[{"data":1,"prerenderedAt":30579},["ShallowReactive",2],{"blog-index-es":3},[4,4405,6100,23469,24117],{"id":5,"title":6,"author":7,"body":8,"date":4386,"description":14,"extension":4387,"image":4388,"lastmod":4386,"meta":4389,"navigation":160,"order":144,"path":4390,"seo":4391,"sitemap":4392,"slug":4395,"stem":4396,"summary":4397,"tags":4398,"__hash__":4404},"content_es\u002Fblog\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis.md","Experimentando con el análisis exploratorio de datos","David Deras",{"type":9,"value":10,"toc":4377},"minimark",[11,15,25,28,31,36,44,52,57,73,875,879,890,941,944,1355,1358,1395,1398,1402,1405,1426,1879,1890,1905,1910,1917,1920,1931,1938,1943,1957,1960,1974,1977,1988,1991,2002,2011,2014,2021,2028,2035,2042,2049,2052,2055,2069,2072,2078,2081,2088,2091,2094,2105,2111,2117,2131,2134,2141,2144,2434,2437,2440,2760,2763,2774,2783,2786,2806,2813,2820,2823,2829,2832,2859,2866,2917,2924,2968,2975,3013,3020,3059,3066,3069,3113,3116,3130,3135,3138,3144,3147,3150,3153,3161,3164,3167,3170,3190,3209,3213,3219,3510,3514,3517,3672,3675,3681,3687,3754,3757,3900,3905,4087,4096,4099,4102,4207,4210,4276,4279,4324,4327,4373],[12,13,14],"p",{},"El análisis exploratorio de datos (EDA) es una etapa crucial en cualquier proyecto de aprendizaje automático. En este articulo realizaremos algunos experimentos con EDA para entender mejor cómo podemos utilizarlo para obtener insights valiosos de nuestros datos y mejorar el rendimiento de nuestros modelos.",[12,16,17,18],{},"Artículo anterior: ",[19,20,24],"a",{"href":21,"rel":22},"https:\u002F\u002Fderas.dev\u002Fes\u002Fblog\u002Fworkflow-machine-learning-projects",[23],"nofollow","El flujo en proyectos de aprendizaje automático",[26,27],"table-of-contents",{},[29,30],"hr",{},[32,33,35],"h2",{"id":34},"un-ejercicio-práctico-estimando-las-ventas-de-una-cafetería","Un Ejercicio Práctico: Estimando las Ventas de una Cafetería",[12,37,38,39,43],{},"Para entender el verdadero impacto de un Análisis Exploratorio de Datos (EDA), salgamos de la teoría y vayamos a la práctica con un escenario comercial: ",[40,41,42],"strong",{},"Estimar cuántos ingresos generará una cafetería al mes",". Este tipo de ejercicios permite que gerentes y dueños de negocio tomen decisiones basadas en datos (Data-Driven) y no en corazonadas.",[12,45,46,47],{},"Puedes seguir este ejercicio interactivo en Google Colab: ",[19,48,51],{"href":49,"rel":50},"https:\u002F\u002Fcolab.research.google.com\u002Fdrive\u002F12NPwGTp9JE0Vl926_ODlqpDRLkbnJimz?usp=sharing",[23],"EDA para Estimar Ventas de una Cafetería",[53,54,56],"h3",{"id":55},"paso-1-generación-y-carga-de-datos","Paso 1: Generación y Carga de Datos",[12,58,59,60,64,65,68,69,72],{},"Como primer paso, necesitamos un historial. Simularemos los datos de 365 días operativos de la cafetería, con variables que van desde la temperatura ambiente hasta inversión en publicidad (Ads en redes sociales). Importamos herramientas esenciales del stack clásico de Python: ",[61,62,63],"code",{},"pandas"," para manejar las tablas, y ",[61,66,67],{},"matplotlib","\u002F",[61,70,71],{},"seaborn"," para gráficos.",[74,75,80],"pre",{"className":76,"code":77,"language":78,"meta":79,"style":79},"language-python shiki shiki-themes vitesse-light vitesse-dark","import pandas as pd\nimport numpy as np\nimport random\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\n# Semilla para que los datos sean reproducibles\nnp.random.seed(42)\nrandom.seed(42)\n\n# Generación del dataset (365 días operativos)\nn = 365\nclimas = [\"Soleado\", \"Lluvioso\", \"Nublado\"]\ndata = []\n\nfor _ in range(n):\n    temperatura = round(random.uniform(15.0, 35.0), 1)\n    inversion_publicidad = round(random.uniform(10.0, 150.0), 2)\n    eventos_cercanos = random.choice([0, 1])\n    descuento_aplicado = random.choice([0, 10, 15, 20])\n    clima = random.choice(climas)\n    \n    # Lógica de negocio (Correlaciones simuladas):\n    # La temperatura baja y los eventos suben ventas. El clima lluvioso invita a tomar café.\n    ventas = (\n        500 + \n        (inversion_publicidad * 2.5) - \n        (temperatura * 8) + \n        (eventos_cercanos * 250) + \n        (descuento_aplicado * 5)\n    )\n    \n    if clima == \"Lluvioso\": ventas += 150\n    elif clima == \"Soleado\": ventas -= 50\n    \n    # Añadimos ruido estadístico para hacerlo realista\n    ventas += np.random.normal(0, 80)\n    \n    data.append([temperatura, inversion_publicidad, eventos_cercanos, descuento_aplicado, clima, round(ventas, 2)])\n\ncolumns = [\"temperatura_c\", \"inversion_publicidad\", \"evento_local\", \"descuento\", \"clima\", \"ventas_diarias\"]\ndf = pd.DataFrame(data, columns=columns)\ndf.head()\n","python","",[61,81,82,101,114,122,142,155,162,169,195,210,215,221,233,277,288,293,317,355,390,419,454,475,481,487,493,504,517,540,559,578,593,599,604,634,660,665,671,701,706,758,763,827,861],{"__ignoreMap":79},[83,84,87,91,95,98],"span",{"class":85,"line":86},"line",1,[83,88,90],{"class":89},"sTPum","import",[83,92,94],{"class":93},"s8w-G"," pandas ",[83,96,97],{"class":89},"as",[83,99,100],{"class":93}," pd\n",[83,102,104,106,109,111],{"class":85,"line":103},2,[83,105,90],{"class":89},[83,107,108],{"class":93}," numpy ",[83,110,97],{"class":89},[83,112,113],{"class":93}," np\n",[83,115,117,119],{"class":85,"line":116},3,[83,118,90],{"class":89},[83,120,121],{"class":93}," random\n",[83,123,125,127,130,134,137,139],{"class":85,"line":124},4,[83,126,90],{"class":89},[83,128,129],{"class":93}," matplotlib",[83,131,133],{"class":132},"si6no",".",[83,135,136],{"class":93},"pyplot ",[83,138,97],{"class":89},[83,140,141],{"class":93}," plt\n",[83,143,145,147,150,152],{"class":85,"line":144},5,[83,146,90],{"class":89},[83,148,149],{"class":93}," seaborn ",[83,151,97],{"class":89},[83,153,154],{"class":93}," sns\n",[83,156,158],{"class":85,"line":157},6,[83,159,161],{"emptyLinePlaceholder":160},true,"\n",[83,163,165],{"class":85,"line":164},7,[83,166,168],{"class":167},"snYqZ","# Semilla para que los datos sean reproducibles\n",[83,170,172,175,177,180,182,185,188,192],{"class":85,"line":171},8,[83,173,174],{"class":93},"np",[83,176,133],{"class":132},[83,178,179],{"class":93},"random",[83,181,133],{"class":132},[83,183,184],{"class":93},"seed",[83,186,187],{"class":132},"(",[83,189,191],{"class":190},"sqbOQ","42",[83,193,194],{"class":132},")\n",[83,196,198,200,202,204,206,208],{"class":85,"line":197},9,[83,199,179],{"class":93},[83,201,133],{"class":132},[83,203,184],{"class":93},[83,205,187],{"class":132},[83,207,191],{"class":190},[83,209,194],{"class":132},[83,211,213],{"class":85,"line":212},10,[83,214,161],{"emptyLinePlaceholder":160},[83,216,218],{"class":85,"line":217},11,[83,219,220],{"class":167},"# Generación del dataset (365 días operativos)\n",[83,222,224,227,230],{"class":85,"line":223},12,[83,225,226],{"class":93},"n ",[83,228,229],{"class":132},"=",[83,231,232],{"class":190}," 365\n",[83,234,236,239,241,244,248,252,254,257,260,263,265,267,269,272,274],{"class":85,"line":235},13,[83,237,238],{"class":93},"climas ",[83,240,229],{"class":132},[83,242,243],{"class":132}," [",[83,245,247],{"class":246},"scnC2","\"",[83,249,251],{"class":250},"spP0B","Soleado",[83,253,247],{"class":246},[83,255,256],{"class":132},",",[83,258,259],{"class":246}," \"",[83,261,262],{"class":250},"Lluvioso",[83,264,247],{"class":246},[83,266,256],{"class":132},[83,268,259],{"class":246},[83,270,271],{"class":250},"Nublado",[83,273,247],{"class":246},[83,275,276],{"class":132},"]\n",[83,278,280,283,285],{"class":85,"line":279},14,[83,281,282],{"class":93},"data ",[83,284,229],{"class":132},[83,286,287],{"class":132}," []\n",[83,289,291],{"class":85,"line":290},15,[83,292,161],{"emptyLinePlaceholder":160},[83,294,296,299,302,305,309,311,314],{"class":85,"line":295},16,[83,297,298],{"class":89},"for",[83,300,301],{"class":93}," _ ",[83,303,304],{"class":89},"in",[83,306,308],{"class":307},"sHLBJ"," range",[83,310,187],{"class":132},[83,312,313],{"class":93},"n",[83,315,316],{"class":132},"):\n",[83,318,320,323,325,328,330,332,334,337,339,342,344,347,350,353],{"class":85,"line":319},17,[83,321,322],{"class":93},"    temperatura ",[83,324,229],{"class":132},[83,326,327],{"class":307}," round",[83,329,187],{"class":132},[83,331,179],{"class":93},[83,333,133],{"class":132},[83,335,336],{"class":93},"uniform",[83,338,187],{"class":132},[83,340,341],{"class":190},"15.0",[83,343,256],{"class":132},[83,345,346],{"class":190}," 35.0",[83,348,349],{"class":132},"),",[83,351,352],{"class":190}," 1",[83,354,194],{"class":132},[83,356,358,361,363,365,367,369,371,373,375,378,380,383,385,388],{"class":85,"line":357},18,[83,359,360],{"class":93},"    inversion_publicidad ",[83,362,229],{"class":132},[83,364,327],{"class":307},[83,366,187],{"class":132},[83,368,179],{"class":93},[83,370,133],{"class":132},[83,372,336],{"class":93},[83,374,187],{"class":132},[83,376,377],{"class":190},"10.0",[83,379,256],{"class":132},[83,381,382],{"class":190}," 150.0",[83,384,349],{"class":132},[83,386,387],{"class":190}," 2",[83,389,194],{"class":132},[83,391,393,396,398,401,403,406,409,412,414,416],{"class":85,"line":392},19,[83,394,395],{"class":93},"    eventos_cercanos ",[83,397,229],{"class":132},[83,399,400],{"class":93}," random",[83,402,133],{"class":132},[83,404,405],{"class":93},"choice",[83,407,408],{"class":132},"([",[83,410,411],{"class":190},"0",[83,413,256],{"class":132},[83,415,352],{"class":190},[83,417,418],{"class":132},"])\n",[83,420,422,425,427,429,431,433,435,437,439,442,444,447,449,452],{"class":85,"line":421},20,[83,423,424],{"class":93},"    descuento_aplicado ",[83,426,229],{"class":132},[83,428,400],{"class":93},[83,430,133],{"class":132},[83,432,405],{"class":93},[83,434,408],{"class":132},[83,436,411],{"class":190},[83,438,256],{"class":132},[83,440,441],{"class":190}," 10",[83,443,256],{"class":132},[83,445,446],{"class":190}," 15",[83,448,256],{"class":132},[83,450,451],{"class":190}," 20",[83,453,418],{"class":132},[83,455,457,460,462,464,466,468,470,473],{"class":85,"line":456},21,[83,458,459],{"class":93},"    clima ",[83,461,229],{"class":132},[83,463,400],{"class":93},[83,465,133],{"class":132},[83,467,405],{"class":93},[83,469,187],{"class":132},[83,471,472],{"class":93},"climas",[83,474,194],{"class":132},[83,476,478],{"class":85,"line":477},22,[83,479,480],{"class":93},"    \n",[83,482,484],{"class":85,"line":483},23,[83,485,486],{"class":167},"    # Lógica de negocio (Correlaciones simuladas):\n",[83,488,490],{"class":85,"line":489},24,[83,491,492],{"class":167},"    # La temperatura baja y los eventos suben ventas. El clima lluvioso invita a tomar café.\n",[83,494,496,499,501],{"class":85,"line":495},25,[83,497,498],{"class":93},"    ventas ",[83,500,229],{"class":132},[83,502,503],{"class":132}," (\n",[83,505,507,510,514],{"class":85,"line":506},26,[83,508,509],{"class":190},"        500",[83,511,513],{"class":512},"s5TCs"," +",[83,515,516],{"class":93}," \n",[83,518,520,523,526,529,532,535,538],{"class":85,"line":519},27,[83,521,522],{"class":132},"        (",[83,524,525],{"class":93},"inversion_publicidad ",[83,527,528],{"class":512},"*",[83,530,531],{"class":190}," 2.5",[83,533,534],{"class":132},")",[83,536,537],{"class":512}," -",[83,539,516],{"class":93},[83,541,543,545,548,550,553,555,557],{"class":85,"line":542},28,[83,544,522],{"class":132},[83,546,547],{"class":93},"temperatura ",[83,549,528],{"class":512},[83,551,552],{"class":190}," 8",[83,554,534],{"class":132},[83,556,513],{"class":512},[83,558,516],{"class":93},[83,560,562,564,567,569,572,574,576],{"class":85,"line":561},29,[83,563,522],{"class":132},[83,565,566],{"class":93},"eventos_cercanos ",[83,568,528],{"class":512},[83,570,571],{"class":190}," 250",[83,573,534],{"class":132},[83,575,513],{"class":512},[83,577,516],{"class":93},[83,579,581,583,586,588,591],{"class":85,"line":580},30,[83,582,522],{"class":132},[83,584,585],{"class":93},"descuento_aplicado ",[83,587,528],{"class":512},[83,589,590],{"class":190}," 5",[83,592,194],{"class":132},[83,594,596],{"class":85,"line":595},31,[83,597,598],{"class":132},"    )\n",[83,600,602],{"class":85,"line":601},32,[83,603,480],{"class":93},[83,605,607,610,613,616,618,620,622,625,628,631],{"class":85,"line":606},33,[83,608,609],{"class":89},"    if",[83,611,612],{"class":93}," clima ",[83,614,615],{"class":512},"==",[83,617,259],{"class":246},[83,619,262],{"class":250},[83,621,247],{"class":246},[83,623,624],{"class":132},":",[83,626,627],{"class":93}," ventas ",[83,629,630],{"class":132},"+=",[83,632,633],{"class":190}," 150\n",[83,635,637,640,642,644,646,648,650,652,654,657],{"class":85,"line":636},34,[83,638,639],{"class":89},"    elif",[83,641,612],{"class":93},[83,643,615],{"class":512},[83,645,259],{"class":246},[83,647,251],{"class":250},[83,649,247],{"class":246},[83,651,624],{"class":132},[83,653,627],{"class":93},[83,655,656],{"class":132},"-=",[83,658,659],{"class":190}," 50\n",[83,661,663],{"class":85,"line":662},35,[83,664,480],{"class":93},[83,666,668],{"class":85,"line":667},36,[83,669,670],{"class":167},"    # Añadimos ruido estadístico para hacerlo realista\n",[83,672,674,676,678,681,683,685,687,690,692,694,696,699],{"class":85,"line":673},37,[83,675,498],{"class":93},[83,677,630],{"class":132},[83,679,680],{"class":93}," np",[83,682,133],{"class":132},[83,684,179],{"class":93},[83,686,133],{"class":132},[83,688,689],{"class":93},"normal",[83,691,187],{"class":132},[83,693,411],{"class":190},[83,695,256],{"class":132},[83,697,698],{"class":190}," 80",[83,700,194],{"class":132},[83,702,704],{"class":85,"line":703},38,[83,705,480],{"class":93},[83,707,709,712,714,717,719,722,724,727,729,732,734,737,739,742,744,746,748,751,753,755],{"class":85,"line":708},39,[83,710,711],{"class":93},"    data",[83,713,133],{"class":132},[83,715,716],{"class":93},"append",[83,718,408],{"class":132},[83,720,721],{"class":93},"temperatura",[83,723,256],{"class":132},[83,725,726],{"class":93}," inversion_publicidad",[83,728,256],{"class":132},[83,730,731],{"class":93}," eventos_cercanos",[83,733,256],{"class":132},[83,735,736],{"class":93}," descuento_aplicado",[83,738,256],{"class":132},[83,740,741],{"class":93}," clima",[83,743,256],{"class":132},[83,745,327],{"class":307},[83,747,187],{"class":132},[83,749,750],{"class":93},"ventas",[83,752,256],{"class":132},[83,754,387],{"class":190},[83,756,757],{"class":132},")])\n",[83,759,761],{"class":85,"line":760},40,[83,762,161],{"emptyLinePlaceholder":160},[83,764,766,769,771,773,775,778,780,782,784,787,789,791,793,796,798,800,802,805,807,809,811,814,816,818,820,823,825],{"class":85,"line":765},41,[83,767,768],{"class":93},"columns ",[83,770,229],{"class":132},[83,772,243],{"class":132},[83,774,247],{"class":246},[83,776,777],{"class":250},"temperatura_c",[83,779,247],{"class":246},[83,781,256],{"class":132},[83,783,259],{"class":246},[83,785,786],{"class":250},"inversion_publicidad",[83,788,247],{"class":246},[83,790,256],{"class":132},[83,792,259],{"class":246},[83,794,795],{"class":250},"evento_local",[83,797,247],{"class":246},[83,799,256],{"class":132},[83,801,259],{"class":246},[83,803,804],{"class":250},"descuento",[83,806,247],{"class":246},[83,808,256],{"class":132},[83,810,259],{"class":246},[83,812,813],{"class":250},"clima",[83,815,247],{"class":246},[83,817,256],{"class":132},[83,819,259],{"class":246},[83,821,822],{"class":250},"ventas_diarias",[83,824,247],{"class":246},[83,826,276],{"class":132},[83,828,830,833,835,838,840,843,845,848,850,854,856,859],{"class":85,"line":829},42,[83,831,832],{"class":93},"df ",[83,834,229],{"class":132},[83,836,837],{"class":93}," pd",[83,839,133],{"class":132},[83,841,842],{"class":93},"DataFrame",[83,844,187],{"class":132},[83,846,847],{"class":93},"data",[83,849,256],{"class":132},[83,851,853],{"class":852},"s9nN2"," columns",[83,855,229],{"class":132},[83,857,858],{"class":93},"columns",[83,860,194],{"class":132},[83,862,864,867,869,872],{"class":85,"line":863},43,[83,865,866],{"class":93},"df",[83,868,133],{"class":132},[83,870,871],{"class":93},"head",[83,873,874],{"class":132},"()\n",[53,876,878],{"id":877},"paso-2-conociendo-la-data-exploración-inicial","Paso 2: Conociendo la Data (Exploración Inicial)",[12,880,881,882,885,886,889],{},"Con ",[61,883,884],{},"df.info()"," comprobamos que no haya datos faltantes (nulos) y los tipos de dato, mientras que ",[61,887,888],{},"df.describe()"," nos resume la media, los máximos y mínimos diarios de ventas y gastos.",[74,891,893],{"className":76,"code":892,"language":78,"meta":79,"style":79},"# Un vistazo rápido a la salud de nuestra tabla\nprint(df.info())\n\n# Estadísticas descriptivas (promedios, cuartiles, mín\u002Fmáx)\nprint(df.describe())\n",[61,894,895,900,917,921,926],{"__ignoreMap":79},[83,896,897],{"class":85,"line":86},[83,898,899],{"class":167},"# Un vistazo rápido a la salud de nuestra tabla\n",[83,901,902,905,907,909,911,914],{"class":85,"line":103},[83,903,904],{"class":307},"print",[83,906,187],{"class":132},[83,908,866],{"class":93},[83,910,133],{"class":132},[83,912,913],{"class":93},"info",[83,915,916],{"class":132},"())\n",[83,918,919],{"class":85,"line":116},[83,920,161],{"emptyLinePlaceholder":160},[83,922,923],{"class":85,"line":124},[83,924,925],{"class":167},"# Estadísticas descriptivas (promedios, cuartiles, mín\u002Fmáx)\n",[83,927,928,930,932,934,936,939],{"class":85,"line":144},[83,929,904],{"class":307},[83,931,187],{"class":132},[83,933,866],{"class":93},[83,935,133],{"class":132},[83,937,938],{"class":93},"describe",[83,940,916],{"class":132},[12,942,943],{},"Dando como resultado lo siguiente:",[74,945,949],{"className":946,"code":947,"language":948,"meta":79,"style":79},"language-sh shiki shiki-themes vitesse-light vitesse-dark","\u003Cclass 'pandas.core.frame.DataFrame'>\nRangeIndex: 365 entries, 0 to 364\nData columns (total 6 columns):\n #   Column         Non-Null Count  Dtype  \n---  ------         --------------  -----  \n 0   temperature_c  365 non-null    float64\n 1   ad_investment  365 non-null    float64\n 2   local_event    365 non-null    int64  \n 3   discount       365 non-null    int64  \n 4   weather        365 non-null    object \n 5   daily_sales    365 non-null    float64\ndtypes: float64(3), int64(2), object(1)\nmemory usage: 17.2+ KB\nNone\n       temperature_c  ad_investment  local_event    discount  daily_sales\ncount     365.000000     365.000000   365.000000  365.000000   365.000000\nmean       24.648767      82.490247     0.561644   11.684932   735.927151\nstd         5.687482      40.828333     0.496867    7.270059   204.863687\nmin        15.100000      10.060000     0.000000    0.000000   226.620000\n25%        19.800000      48.400000     0.000000   10.000000   576.890000\n50%        24.500000      84.780000     1.000000   15.000000   729.730000\n75%        29.600000     120.280000     1.000000   20.000000   879.280000\nmax        35.000000     149.780000     1.000000   20.000000  1337.220000\n","sh",[61,950,951,970,991,1008,1013,1031,1047,1060,1077,1094,1112,1125,1164,1178,1183,1200,1219,1239,1259,1279,1298,1318,1337],{"__ignoreMap":79},[83,952,953,956,959,962,965,967],{"class":85,"line":86},[83,954,955],{"class":512},"\u003C",[83,957,958],{"class":93},"class ",[83,960,961],{"class":246},"'",[83,963,964],{"class":250},"pandas.core.frame.DataFrame",[83,966,961],{"class":246},[83,968,969],{"class":512},">\n",[83,971,972,976,979,982,985,988],{"class":85,"line":103},[83,973,975],{"class":974},"s_xSY","RangeIndex:",[83,977,978],{"class":190}," 365",[83,980,981],{"class":250}," entries,",[83,983,984],{"class":190}," 0",[83,986,987],{"class":250}," to",[83,989,990],{"class":190}," 364\n",[83,992,993,996,998,1001,1004,1006],{"class":85,"line":116},[83,994,995],{"class":974},"Data",[83,997,853],{"class":250},[83,999,1000],{"class":93}," (total ",[83,1002,1003],{"class":190},"6",[83,1005,853],{"class":250},[83,1007,316],{"class":93},[83,1009,1010],{"class":85,"line":124},[83,1011,1012],{"class":167}," #   Column         Non-Null Count  Dtype  \n",[83,1014,1015,1018,1022,1025,1028],{"class":85,"line":144},[83,1016,1017],{"class":974},"---",[83,1019,1021],{"class":1020},"sfsYZ","  ------",[83,1023,1024],{"class":1020},"         --------------",[83,1026,1027],{"class":1020},"  -----",[83,1029,1030],{"class":93},"  \n",[83,1032,1033,1035,1038,1041,1044],{"class":85,"line":157},[83,1034,984],{"class":974},[83,1036,1037],{"class":250},"   temperature_c",[83,1039,1040],{"class":190},"  365",[83,1042,1043],{"class":250}," non-null",[83,1045,1046],{"class":250},"    float64\n",[83,1048,1049,1051,1054,1056,1058],{"class":85,"line":164},[83,1050,352],{"class":974},[83,1052,1053],{"class":250},"   ad_investment",[83,1055,1040],{"class":190},[83,1057,1043],{"class":250},[83,1059,1046],{"class":250},[83,1061,1062,1064,1067,1070,1072,1075],{"class":85,"line":171},[83,1063,387],{"class":974},[83,1065,1066],{"class":250},"   local_event",[83,1068,1069],{"class":190},"    365",[83,1071,1043],{"class":250},[83,1073,1074],{"class":250},"    int64",[83,1076,1030],{"class":93},[83,1078,1079,1082,1085,1088,1090,1092],{"class":85,"line":197},[83,1080,1081],{"class":974}," 3",[83,1083,1084],{"class":250},"   discount",[83,1086,1087],{"class":190},"       365",[83,1089,1043],{"class":250},[83,1091,1074],{"class":250},[83,1093,1030],{"class":93},[83,1095,1096,1099,1102,1105,1107,1110],{"class":85,"line":212},[83,1097,1098],{"class":974}," 4",[83,1100,1101],{"class":250},"   weather",[83,1103,1104],{"class":190},"        365",[83,1106,1043],{"class":250},[83,1108,1109],{"class":250},"    object",[83,1111,516],{"class":93},[83,1113,1114,1116,1119,1121,1123],{"class":85,"line":217},[83,1115,590],{"class":974},[83,1117,1118],{"class":250},"   daily_sales",[83,1120,1069],{"class":190},[83,1122,1043],{"class":250},[83,1124,1046],{"class":250},[83,1126,1127,1130,1133,1135,1138,1140,1142,1145,1147,1150,1152,1154,1157,1159,1162],{"class":85,"line":223},[83,1128,1129],{"class":974},"dtypes:",[83,1131,1132],{"class":250}," float64",[83,1134,187],{"class":132},[83,1136,1137],{"class":974},"3",[83,1139,534],{"class":132},[83,1141,256],{"class":250},[83,1143,1144],{"class":250}," int64",[83,1146,187],{"class":132},[83,1148,1149],{"class":974},"2",[83,1151,534],{"class":132},[83,1153,256],{"class":250},[83,1155,1156],{"class":250}," object",[83,1158,187],{"class":132},[83,1160,1161],{"class":974},"1",[83,1163,194],{"class":132},[83,1165,1166,1169,1172,1175],{"class":85,"line":235},[83,1167,1168],{"class":974},"memory",[83,1170,1171],{"class":250}," usage:",[83,1173,1174],{"class":250}," 17.2+",[83,1176,1177],{"class":250}," KB\n",[83,1179,1180],{"class":85,"line":279},[83,1181,1182],{"class":974},"None\n",[83,1184,1185,1188,1191,1194,1197],{"class":85,"line":290},[83,1186,1187],{"class":974},"       temperature_c",[83,1189,1190],{"class":250},"  ad_investment",[83,1192,1193],{"class":250},"  local_event",[83,1195,1196],{"class":250},"    discount",[83,1198,1199],{"class":250},"  daily_sales\n",[83,1201,1202,1205,1208,1210,1213,1216],{"class":85,"line":295},[83,1203,1204],{"class":974},"count",[83,1206,1207],{"class":190},"     365.000000",[83,1209,1207],{"class":190},[83,1211,1212],{"class":190},"   365.000000",[83,1214,1215],{"class":190},"  365.000000",[83,1217,1218],{"class":190},"   365.000000\n",[83,1220,1221,1224,1227,1230,1233,1236],{"class":85,"line":319},[83,1222,1223],{"class":974},"mean",[83,1225,1226],{"class":190},"       24.648767",[83,1228,1229],{"class":190},"      82.490247",[83,1231,1232],{"class":190},"     0.561644",[83,1234,1235],{"class":190},"   11.684932",[83,1237,1238],{"class":190},"   735.927151\n",[83,1240,1241,1244,1247,1250,1253,1256],{"class":85,"line":357},[83,1242,1243],{"class":974},"std",[83,1245,1246],{"class":190},"         5.687482",[83,1248,1249],{"class":190},"      40.828333",[83,1251,1252],{"class":190},"     0.496867",[83,1254,1255],{"class":190},"    7.270059",[83,1257,1258],{"class":190},"   204.863687\n",[83,1260,1261,1264,1267,1270,1273,1276],{"class":85,"line":392},[83,1262,1263],{"class":974},"min",[83,1265,1266],{"class":190},"        15.100000",[83,1268,1269],{"class":190},"      10.060000",[83,1271,1272],{"class":190},"     0.000000",[83,1274,1275],{"class":190},"    0.000000",[83,1277,1278],{"class":190},"   226.620000\n",[83,1280,1281,1284,1287,1290,1292,1295],{"class":85,"line":421},[83,1282,1283],{"class":974},"25%",[83,1285,1286],{"class":190},"        19.800000",[83,1288,1289],{"class":190},"      48.400000",[83,1291,1272],{"class":190},[83,1293,1294],{"class":190},"   10.000000",[83,1296,1297],{"class":190},"   576.890000\n",[83,1299,1300,1303,1306,1309,1312,1315],{"class":85,"line":456},[83,1301,1302],{"class":974},"50%",[83,1304,1305],{"class":190},"        24.500000",[83,1307,1308],{"class":190},"      84.780000",[83,1310,1311],{"class":190},"     1.000000",[83,1313,1314],{"class":190},"   15.000000",[83,1316,1317],{"class":190},"   729.730000\n",[83,1319,1320,1323,1326,1329,1331,1334],{"class":85,"line":477},[83,1321,1322],{"class":974},"75%",[83,1324,1325],{"class":190},"        29.600000",[83,1327,1328],{"class":190},"     120.280000",[83,1330,1311],{"class":190},[83,1332,1333],{"class":190},"   20.000000",[83,1335,1336],{"class":190},"   879.280000\n",[83,1338,1339,1342,1345,1348,1350,1352],{"class":85,"line":483},[83,1340,1341],{"class":974},"max",[83,1343,1344],{"class":190},"        35.000000",[83,1346,1347],{"class":190},"     149.780000",[83,1349,1311],{"class":190},[83,1351,1333],{"class":190},[83,1353,1354],{"class":190},"  1337.220000\n",[12,1356,1357],{},"Exploremos un poco los resultados:",[1359,1360,1361,1365,1375,1378,1381],"ul",{},[1362,1363,1364],"li",{},"La temperatura promedio es de 24.65°C, con un rango entre 15.1°C y 35°C.",[1362,1366,1367,1368,1371,1372,133],{},"La inversión en publicidad varía ampliamente, con un promedio de ",[61,1369,1370],{},"$82.49"," y un máximo de ",[61,1373,1374],{},"$149.78",[1362,1376,1377],{},"El 56.16% de los días tuvieron un evento local.",[1362,1379,1380],{},"El descuento aplicado varía, con un promedio de 11.68% y un máximo de 20%.",[1362,1382,1383,1384,1387,1388,1391,1392,133],{},"Las ventas diarias tienen un promedio de ",[61,1385,1386],{},"$735.93",", con una amplia variabilidad, desde un mínimo de ",[61,1389,1390],{},"$226.62"," hasta un máximo de ",[61,1393,1394],{},"$1337.22",[12,1396,1397],{},"Además, no hay valores nulos en el dataset, lo que es una buena señal para el análisis posterior.\nLa amplia variabilidad en las ventas diarias sugiere que hay factores significativos que afectan las ventas, lo que hace que el análisis exploratorio de datos sea aún más crucial para entender estas relaciones.",[53,1399,1401],{"id":1400},"paso-3-visualización-estratégica","Paso 3: Visualización Estratégica",[12,1403,1404],{},"La mejor forma de entender nuestros datos es a través de la visualización. Vamos a construir tres gráficos clave para nuestro análisis:",[1406,1407,1408,1414,1420],"ol",{},[1362,1409,1410,1413],{},[40,1411,1412],{},"Histograma de Ventas:"," Nos dice si nuestras ganancias diarias siguen una curva normal (Campana de Gauss) o si están sesgadas.",[1362,1415,1416,1419],{},[40,1417,1418],{},"Dispersión (Scatter) Publicidad vs. Ventas:"," Revela si meter más dinero a los Ads realmente sube las ventas o si llega a un tope (rendimiento decreciente).",[1362,1421,1422,1425],{},[40,1423,1424],{},"Matriz de Correlación:"," Es el \"santo grial\" del EDA. Asignará un valor de -1 a 1 a la relación entre todas nuestras variables.",[74,1427,1429],{"className":76,"code":1428,"language":78,"meta":79,"style":79},"# 1. Distribución de las ventas (¿vendemos más en días \"buenos\" o \"malos\" estadísticamente?)\nplt.figure(figsize=(8,5))\nsns.histplot(df[\"ventas_diarias\"], bins=20, kde=True, color=\"brown\")\nplt.title(\"Distribución de las Ventas Diarias de Café\")\nplt.xlabel(\"Ventas en $\")\nplt.ylabel(\"Frecuencia (Días)\")\nplt.show()\n\n# 2. El impacto de los Ads\nplt.figure(figsize=(8,5))\nsns.scatterplot(x=\"inversion_publicidad\", y=\"ventas_diarias\", hue=\"clima\", data=df)\nplt.title(\"Inversión en Publicidad vs. Ventas (Coloreado por Clima)\")\nplt.xlabel(\"Inversión ($)\")\nplt.ylabel(\"Ventas ($)\")\nplt.show()\n\n# 3. El mapa de calor (Heatmap)\nplt.figure(figsize=(8,6))\nsns.heatmap(df.corr(numeric_only=True), annot=True, cmap=\"YlOrBr\", fmt=\".2f\")\nplt.title(\"Correlación de Variables\")\nplt.show()\n",[61,1430,1431,1436,1465,1525,1545,1565,1585,1596,1600,1605,1627,1686,1705,1724,1743,1753,1757,1762,1784,1850,1869],{"__ignoreMap":79},[83,1432,1433],{"class":85,"line":86},[83,1434,1435],{"class":167},"# 1. Distribución de las ventas (¿vendemos más en días \"buenos\" o \"malos\" estadísticamente?)\n",[83,1437,1438,1441,1443,1446,1448,1451,1454,1457,1459,1462],{"class":85,"line":103},[83,1439,1440],{"class":93},"plt",[83,1442,133],{"class":132},[83,1444,1445],{"class":93},"figure",[83,1447,187],{"class":132},[83,1449,1450],{"class":852},"figsize",[83,1452,1453],{"class":132},"=(",[83,1455,1456],{"class":190},"8",[83,1458,256],{"class":132},[83,1460,1461],{"class":190},"5",[83,1463,1464],{"class":132},"))\n",[83,1466,1467,1470,1472,1475,1477,1479,1482,1484,1486,1488,1491,1494,1496,1499,1501,1504,1506,1509,1511,1514,1516,1518,1521,1523],{"class":85,"line":116},[83,1468,1469],{"class":93},"sns",[83,1471,133],{"class":132},[83,1473,1474],{"class":93},"histplot",[83,1476,187],{"class":132},[83,1478,866],{"class":93},[83,1480,1481],{"class":132},"[",[83,1483,247],{"class":246},[83,1485,822],{"class":250},[83,1487,247],{"class":246},[83,1489,1490],{"class":132},"],",[83,1492,1493],{"class":852}," bins",[83,1495,229],{"class":132},[83,1497,1498],{"class":190},"20",[83,1500,256],{"class":132},[83,1502,1503],{"class":852}," kde",[83,1505,229],{"class":132},[83,1507,1508],{"class":89},"True",[83,1510,256],{"class":132},[83,1512,1513],{"class":852}," color",[83,1515,229],{"class":132},[83,1517,247],{"class":246},[83,1519,1520],{"class":250},"brown",[83,1522,247],{"class":246},[83,1524,194],{"class":132},[83,1526,1527,1529,1531,1534,1536,1538,1541,1543],{"class":85,"line":124},[83,1528,1440],{"class":93},[83,1530,133],{"class":132},[83,1532,1533],{"class":93},"title",[83,1535,187],{"class":132},[83,1537,247],{"class":246},[83,1539,1540],{"class":250},"Distribución de las Ventas Diarias de Café",[83,1542,247],{"class":246},[83,1544,194],{"class":132},[83,1546,1547,1549,1551,1554,1556,1558,1561,1563],{"class":85,"line":144},[83,1548,1440],{"class":93},[83,1550,133],{"class":132},[83,1552,1553],{"class":93},"xlabel",[83,1555,187],{"class":132},[83,1557,247],{"class":246},[83,1559,1560],{"class":250},"Ventas en $",[83,1562,247],{"class":246},[83,1564,194],{"class":132},[83,1566,1567,1569,1571,1574,1576,1578,1581,1583],{"class":85,"line":157},[83,1568,1440],{"class":93},[83,1570,133],{"class":132},[83,1572,1573],{"class":93},"ylabel",[83,1575,187],{"class":132},[83,1577,247],{"class":246},[83,1579,1580],{"class":250},"Frecuencia (Días)",[83,1582,247],{"class":246},[83,1584,194],{"class":132},[83,1586,1587,1589,1591,1594],{"class":85,"line":164},[83,1588,1440],{"class":93},[83,1590,133],{"class":132},[83,1592,1593],{"class":93},"show",[83,1595,874],{"class":132},[83,1597,1598],{"class":85,"line":171},[83,1599,161],{"emptyLinePlaceholder":160},[83,1601,1602],{"class":85,"line":197},[83,1603,1604],{"class":167},"# 2. El impacto de los Ads\n",[83,1606,1607,1609,1611,1613,1615,1617,1619,1621,1623,1625],{"class":85,"line":212},[83,1608,1440],{"class":93},[83,1610,133],{"class":132},[83,1612,1445],{"class":93},[83,1614,187],{"class":132},[83,1616,1450],{"class":852},[83,1618,1453],{"class":132},[83,1620,1456],{"class":190},[83,1622,256],{"class":132},[83,1624,1461],{"class":190},[83,1626,1464],{"class":132},[83,1628,1629,1631,1633,1636,1638,1641,1643,1645,1647,1649,1651,1654,1656,1658,1660,1662,1664,1667,1669,1671,1673,1675,1677,1680,1682,1684],{"class":85,"line":217},[83,1630,1469],{"class":93},[83,1632,133],{"class":132},[83,1634,1635],{"class":93},"scatterplot",[83,1637,187],{"class":132},[83,1639,1640],{"class":852},"x",[83,1642,229],{"class":132},[83,1644,247],{"class":246},[83,1646,786],{"class":250},[83,1648,247],{"class":246},[83,1650,256],{"class":132},[83,1652,1653],{"class":852}," y",[83,1655,229],{"class":132},[83,1657,247],{"class":246},[83,1659,822],{"class":250},[83,1661,247],{"class":246},[83,1663,256],{"class":132},[83,1665,1666],{"class":852}," hue",[83,1668,229],{"class":132},[83,1670,247],{"class":246},[83,1672,813],{"class":250},[83,1674,247],{"class":246},[83,1676,256],{"class":132},[83,1678,1679],{"class":852}," data",[83,1681,229],{"class":132},[83,1683,866],{"class":93},[83,1685,194],{"class":132},[83,1687,1688,1690,1692,1694,1696,1698,1701,1703],{"class":85,"line":223},[83,1689,1440],{"class":93},[83,1691,133],{"class":132},[83,1693,1533],{"class":93},[83,1695,187],{"class":132},[83,1697,247],{"class":246},[83,1699,1700],{"class":250},"Inversión en Publicidad vs. Ventas (Coloreado por Clima)",[83,1702,247],{"class":246},[83,1704,194],{"class":132},[83,1706,1707,1709,1711,1713,1715,1717,1720,1722],{"class":85,"line":235},[83,1708,1440],{"class":93},[83,1710,133],{"class":132},[83,1712,1553],{"class":93},[83,1714,187],{"class":132},[83,1716,247],{"class":246},[83,1718,1719],{"class":250},"Inversión ($)",[83,1721,247],{"class":246},[83,1723,194],{"class":132},[83,1725,1726,1728,1730,1732,1734,1736,1739,1741],{"class":85,"line":279},[83,1727,1440],{"class":93},[83,1729,133],{"class":132},[83,1731,1573],{"class":93},[83,1733,187],{"class":132},[83,1735,247],{"class":246},[83,1737,1738],{"class":250},"Ventas ($)",[83,1740,247],{"class":246},[83,1742,194],{"class":132},[83,1744,1745,1747,1749,1751],{"class":85,"line":290},[83,1746,1440],{"class":93},[83,1748,133],{"class":132},[83,1750,1593],{"class":93},[83,1752,874],{"class":132},[83,1754,1755],{"class":85,"line":295},[83,1756,161],{"emptyLinePlaceholder":160},[83,1758,1759],{"class":85,"line":319},[83,1760,1761],{"class":167},"# 3. El mapa de calor (Heatmap)\n",[83,1763,1764,1766,1768,1770,1772,1774,1776,1778,1780,1782],{"class":85,"line":357},[83,1765,1440],{"class":93},[83,1767,133],{"class":132},[83,1769,1445],{"class":93},[83,1771,187],{"class":132},[83,1773,1450],{"class":852},[83,1775,1453],{"class":132},[83,1777,1456],{"class":190},[83,1779,256],{"class":132},[83,1781,1003],{"class":190},[83,1783,1464],{"class":132},[83,1785,1786,1788,1790,1793,1795,1797,1799,1802,1804,1807,1809,1811,1813,1816,1818,1820,1822,1825,1827,1829,1832,1834,1836,1839,1841,1843,1846,1848],{"class":85,"line":392},[83,1787,1469],{"class":93},[83,1789,133],{"class":132},[83,1791,1792],{"class":93},"heatmap",[83,1794,187],{"class":132},[83,1796,866],{"class":93},[83,1798,133],{"class":132},[83,1800,1801],{"class":93},"corr",[83,1803,187],{"class":132},[83,1805,1806],{"class":852},"numeric_only",[83,1808,229],{"class":132},[83,1810,1508],{"class":89},[83,1812,349],{"class":132},[83,1814,1815],{"class":852}," annot",[83,1817,229],{"class":132},[83,1819,1508],{"class":89},[83,1821,256],{"class":132},[83,1823,1824],{"class":852}," cmap",[83,1826,229],{"class":132},[83,1828,247],{"class":246},[83,1830,1831],{"class":250},"YlOrBr",[83,1833,247],{"class":246},[83,1835,256],{"class":132},[83,1837,1838],{"class":852}," fmt",[83,1840,229],{"class":132},[83,1842,247],{"class":246},[83,1844,1845],{"class":250},".2f",[83,1847,247],{"class":246},[83,1849,194],{"class":132},[83,1851,1852,1854,1856,1858,1860,1862,1865,1867],{"class":85,"line":421},[83,1853,1440],{"class":93},[83,1855,133],{"class":132},[83,1857,1533],{"class":93},[83,1859,187],{"class":132},[83,1861,247],{"class":246},[83,1863,1864],{"class":250},"Correlación de Variables",[83,1866,247],{"class":246},[83,1868,194],{"class":132},[83,1870,1871,1873,1875,1877],{"class":85,"line":456},[83,1872,1440],{"class":93},[83,1874,133],{"class":132},[83,1876,1593],{"class":93},[83,1878,874],{"class":132},[12,1880,1881,1886],{},[1882,1883],"img",{"alt":1884,"src":1885},"Distribución de ventas diarias","\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis\u002Fshared\u002Fsales_distribution.webp",[1887,1888,1889],"em",{},"Histograma de Ventas",[12,1891,1892,1893,1896,1897,1900,1901,1904],{},"Comencemos con el ",[40,1894,1895],{},"histograma",", que nos permite visualizar cómo se distribuyen las ventas diarias a lo largo del tiempo. En este caso, observamos que las ventas siguen una ",[40,1898,1899],{},"distribución aproximadamente normal",", con una media cercana a ",[61,1902,1903],{},"$800",". Esto significa que la mayoría de los días las ventas se concentran alrededor de ese valor promedio, y que los días con ventas muy bajas o muy altas son menos frecuentes y se distribuyen de manera relativamente simétrica a ambos lados.",[1359,1906,1907],{},[1362,1908,1909],{},"¿Por qué es importante identificar una distribución normal?",[12,1911,1912,1913,1916],{},"Porque muchos modelos estadísticos y de machine learning, como la ",[40,1914,1915],{},"regresión lineal",", el análisis de varianza o ciertos modelos probabilísticos, funcionan mejor cuando los datos (o al menos los errores del modelo) siguen una distribución normal.",[12,1918,1919],{},"Cuando esta condición se cumple:",[1359,1921,1922,1925,1928],{},[1362,1923,1924],{},"Las estimaciones tienden a ser más estables.",[1362,1926,1927],{},"Los intervalos de confianza y pruebas estadísticas son más confiables.",[1362,1929,1930],{},"El modelo no se ve excesivamente afectado por valores extremos.",[12,1932,1933,1934,1937],{},"Si los datos ",[40,1935,1936],{},"no"," siguen una distribución normal, puede ser necesario aplicar transformaciones matemáticas (como logaritmo, raíz cuadrada o Box-Cox) para estabilizar la varianza y reducir la asimetría.",[1359,1939,1940],{},[1362,1941,1942],{},"¿Qué significa \"sesgo a la derecha\" o \"sesgo a la izquierda\"?",[1359,1944,1945,1951],{},[1362,1946,1947,1950],{},[40,1948,1949],{},"Sesgo a la derecha (asimetría positiva):"," Hay una cola larga hacia valores altos. Esto indica que existen pocos días con ventas extremadamente altas.",[1362,1952,1953,1956],{},[40,1954,1955],{},"Sesgo a la izquierda (asimetría negativa):"," Hay una cola larga hacia valores bajos. Esto indica que existen pocos días con ventas inusualmente bajas.",[12,1958,1959],{},"La asimetría es importante porque los modelos sensibles a valores extremos pueden verse distorsionados.",[12,1961,1962,1963,1966,1967,1970,1971,133],{},"Supongamos que la mayoría de los días las ventas están entre ",[61,1964,1965],{},"$700"," y ",[61,1968,1969],{},"$900",", pero en tres días especiales (por ejemplo, promociones o feriados) las ventas alcanzan ",[61,1972,1973],{},"$2,500",[12,1975,1976],{},"Si entrenamos una regresión lineal directamente con esos datos:",[1359,1978,1979,1982,1985],{},[1362,1980,1981],{},"El modelo intentará ajustar una línea que también explique esos picos.",[1362,1983,1984],{},"Esto puede desplazar la pendiente o el intercepto.",[1362,1986,1987],{},"Como resultado, las predicciones para los días “normales” (que son la mayoría) podrían quedar ligeramente infladas.",[12,1989,1990],{},"En cambio, si aplicamos una transformación logarítmica antes de entrenar el modelo:",[1359,1992,1993,1996,1999],{},[1362,1994,1995],{},"Se reduce el impacto de los valores extremadamente altos.",[1362,1997,1998],{},"La distribución se vuelve más simétrica.",[1362,2000,2001],{},"El modelo aprende un patrón más representativo del comportamiento general.",[12,2003,2004,2008],{},[1882,2005],{"alt":2006,"src":2007},"Publicidad vs Ventas","\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis\u002Fshared\u002Fads_vs_sales.webp",[1887,2009,2010],{},"Dispersión entre Inversión en Publicidad y Ventas",[12,2012,2013],{},"Los puntos según el clima son de diferentes colores: Azul-Soleado, Naranja-Nublado, Verde-Lluvioso",[1359,2015,2016],{},[1362,2017,2018],{},[40,2019,2020],{},"Relación principal: inversión vs. ventas",[12,2022,2023,2024,2027],{},"Lo primero que se observa es una ",[40,2025,2026],{},"tendencia positiva",":\nA medida que aumenta la inversión en publicidad, las ventas tienden a aumentar.",[12,2029,2030,2031,2034],{},"Esto indica una ",[40,2032,2033],{},"correlación positiva"," entre ambas variables. No parece una relación completamente aleatoria; los puntos muestran una pendiente ascendente general.",[12,2036,2037,2038,2041],{},"En términos de machine learning, esto sugiere que la inversión publicitaria es ",[40,2039,2040],{},"una"," variable predictora relevante para estimar ventas (no la única).",[1359,2043,2044],{},[1362,2045,2046],{},[40,2047,2048],{},"Variabilidad en las ventas",[12,2050,2051],{},"Aunque la tendencia es positiva, los puntos están bastante dispersos verticalmente.",[12,2053,2054],{},"Por ejemplo:",[12,2056,2057,2058,2061,2062,1966,2065,2068],{},"Con una inversión de ",[61,2059,2060],{},"$100",", las ventas pueden variar entre aproximadamente ",[61,2063,2064],{},"$400",[61,2066,2067],{},"$1,100"," dependiendo de otros factores.",[12,2070,2071],{},"Esto nos dice algo muy importante:",[2073,2074,2075],"blockquote",{},[12,2076,2077],{},"La inversión no explica el 100% del comportamiento de las ventas.",[12,2079,2080],{},"Existen otras variables influyendo (en este caso, sabemos que el clima es una de ellas).",[1359,2082,2083],{},[1362,2084,2085],{},[40,2086,2087],{},"Impacto del clima",[12,2089,2090],{},"Aquí es donde el gráfico se vuelve más interesante.",[12,2092,2093],{},"Observando los colores:",[1359,2095,2096,2099,2102],{},[1362,2097,2098],{},"Los puntos verdes (lluvioso) tienden a ubicarse en valores de ventas más altos.",[1362,2100,2101],{},"Los puntos azules (soleado) tienden a concentrarse en valores más bajos para el mismo nivel de inversión.",[1362,2103,2104],{},"Los naranjas (nublado) están en un punto intermedio.",[12,2106,2107,2108,133],{},"Esto sugiere que el clima actúa como una ",[40,2109,2110],{},"variable moderadora",[12,2112,2113,2114,624],{},"Por ejemplo:\nCon una inversión de ",[61,2115,2116],{},"$120",[1359,2118,2119,2125],{},[1362,2120,2121,2122],{},"Día soleado → ventas alrededor de ",[61,2123,2124],{},"$500–900",[1362,2126,2127,2128],{},"Día lluvioso → ventas alrededor de ",[61,2129,2130],{},"$700–1,200",[12,2132,2133],{},"En un modelo de regresión simple que solo use inversión, estas diferencias generarían errores grandes.",[1359,2135,2136],{},[1362,2137,2138],{},[40,2139,2140],{},"Implicación para modelado",[12,2142,2143],{},"Si entrenamos un modelo usando solo inversión:",[83,2145,2148],{"className":2146},[2147],"katex-display",[83,2149,2152,2218],{"className":2150},[2151],"katex",[83,2153,2156],{"className":2154},[2155],"katex-mathml",[2157,2158,2161],"math",{"xmlns":2159,"display":2160},"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML","block",[2162,2163,2164,2213],"semantics",{},[2165,2166,2167,2171,2174,2184,2187,2193,2196],"mrow",{},[2168,2169,2170],"mtext",{},"Ventas",[2172,2173,229],"mo",{},[2175,2176,2177,2181],"msub",{},[2178,2179,2180],"mi",{},"β",[2182,2183,411],"mn",{},[2172,2185,2186],{},"+",[2175,2188,2189,2191],{},[2178,2190,2180],{},[2182,2192,1161],{},[2172,2194,2195],{},"⋅",[2165,2197,2198,2201,2211],{},[2168,2199,2200],{},"Inversi",[2202,2203,2205,2208],"mover",{"accent":2204},"true",[2168,2206,2207],{},"o",[2172,2209,2210],{},"ˊ",[2168,2212,313],{},[2214,2215,2217],"annotation",{"encoding":2216},"application\u002Fx-tex","\\text{Ventas} = \\beta_0 + \\beta_1 \\cdot \\text{Inversión}",[83,2219,2222,2251,2327,2382],{"className":2220,"ariaHidden":2204},[2221],"katex-html",[83,2223,2226,2231,2239,2244,2248],{"className":2224},[2225],"base",[83,2227],{"className":2228,"style":2230},[2229],"strut","height:0.6833em;",[83,2232,2236],{"className":2233},[2234,2235],"mord","text",[83,2237,2170],{"className":2238},[2234],[83,2240],{"className":2241,"style":2243},[2242],"mspace","margin-right:0.2778em;",[83,2245,229],{"className":2246},[2247],"mrel",[83,2249],{"className":2250,"style":2243},[2242],[83,2252,2254,2258,2316,2320,2324],{"className":2253},[2225],[83,2255],{"className":2256,"style":2257},[2229],"height:0.8889em;vertical-align:-0.1944em;",[83,2259,2261,2266],{"className":2260},[2234],[83,2262,2180],{"className":2263,"style":2265},[2234,2264],"mathnormal","margin-right:0.0528em;",[83,2267,2270],{"className":2268},[2269],"msupsub",[83,2271,2275,2307],{"className":2272},[2273,2274],"vlist-t","vlist-t2",[83,2276,2279,2302],{"className":2277},[2278],"vlist-r",[83,2280,2284],{"className":2281,"style":2283},[2282],"vlist","height:0.3011em;",[83,2285,2287,2292],{"style":2286},"top:-2.55em;margin-left:-0.0528em;margin-right:0.05em;",[83,2288],{"className":2289,"style":2291},[2290],"pstrut","height:2.7em;",[83,2293,2299],{"className":2294},[2295,2296,2297,2298],"sizing","reset-size6","size3","mtight",[83,2300,411],{"className":2301},[2234,2298],[83,2303,2306],{"className":2304},[2305],"vlist-s","​",[83,2308,2310],{"className":2309},[2278],[83,2311,2314],{"className":2312,"style":2313},[2282],"height:0.15em;",[83,2315],{},[83,2317],{"className":2318,"style":2319},[2242],"margin-right:0.2222em;",[83,2321,2186],{"className":2322},[2323],"mbin",[83,2325],{"className":2326,"style":2319},[2242],[83,2328,2330,2333,2373,2376,2379],{"className":2329},[2225],[83,2331],{"className":2332,"style":2257},[2229],[83,2334,2336,2339],{"className":2335},[2234],[83,2337,2180],{"className":2338,"style":2265},[2234,2264],[83,2340,2342],{"className":2341},[2269],[83,2343,2345,2365],{"className":2344},[2273,2274],[83,2346,2348,2362],{"className":2347},[2278],[83,2349,2351],{"className":2350,"style":2283},[2282],[83,2352,2353,2356],{"style":2286},[83,2354],{"className":2355,"style":2291},[2290],[83,2357,2359],{"className":2358},[2295,2296,2297,2298],[83,2360,1161],{"className":2361},[2234,2298],[83,2363,2306],{"className":2364},[2305],[83,2366,2368],{"className":2367},[2278],[83,2369,2371],{"className":2370,"style":2313},[2282],[83,2372],{},[83,2374],{"className":2375,"style":2319},[2242],[83,2377,2195],{"className":2378},[2323],[83,2380],{"className":2381,"style":2319},[2242],[83,2383,2385,2389],{"className":2384},[2225],[83,2386],{"className":2387,"style":2388},[2229],"height:0.6944em;",[83,2390,2392,2395,2431],{"className":2391},[2234,2235],[83,2393,2200],{"className":2394},[2234],[83,2396,2399],{"className":2397},[2234,2398],"accent",[83,2400,2402],{"className":2401},[2273],[83,2403,2405],{"className":2404},[2278],[83,2406,2408,2418],{"className":2407,"style":2388},[2282],[83,2409,2411,2415],{"style":2410},"top:-3em;",[83,2412],{"className":2413,"style":2414},[2290],"height:3em;",[83,2416,2207],{"className":2417},[2234],[83,2419,2420,2423],{"style":2410},[83,2421],{"className":2422,"style":2414},[2290],[83,2424,2428],{"className":2425,"style":2427},[2426],"accent-body","left:-0.25em;",[83,2429,2210],{"className":2430},[2234],[83,2432,313],{"className":2433},[2234],[12,2435,2436],{},"El modelo capturará la tendencia general, pero tendrá errores sistemáticos dependiendo del clima.",[12,2438,2439],{},"En cambio, si incluimos el clima como variable categórica (por ejemplo usando one-hot encoding):",[83,2441,2443],{"className":2442},[2147],[83,2444,2446,2503],{"className":2445},[2151],[83,2447,2449],{"className":2448},[2155],[2157,2450,2451],{"xmlns":2159,"display":2160},[2162,2452,2453,2500],{},[2165,2454,2455,2457,2459,2465,2467,2473,2475,2487,2489,2495,2497],{},[2168,2456,2170],{},[2172,2458,229],{},[2175,2460,2461,2463],{},[2178,2462,2180],{},[2182,2464,411],{},[2172,2466,2186],{},[2175,2468,2469,2471],{},[2178,2470,2180],{},[2182,2472,1161],{},[2172,2474,2195],{},[2165,2476,2477,2479,2485],{},[2168,2478,2200],{},[2202,2480,2481,2483],{"accent":2204},[2168,2482,2207],{},[2172,2484,2210],{},[2168,2486,313],{},[2172,2488,2186],{},[2175,2490,2491,2493],{},[2178,2492,2180],{},[2182,2494,1149],{},[2172,2496,2195],{},[2168,2498,2499],{},"Clima",[2214,2501,2502],{"encoding":2216},"\\text{Ventas} = \\beta_0 + \\beta_1 \\cdot \\text{Inversión} + \\beta_2 \\cdot \\text{Clima}",[83,2504,2506,2527,2582,2637,2693,2748],{"className":2505,"ariaHidden":2204},[2221],[83,2507,2509,2512,2518,2521,2524],{"className":2508},[2225],[83,2510],{"className":2511,"style":2230},[2229],[83,2513,2515],{"className":2514},[2234,2235],[83,2516,2170],{"className":2517},[2234],[83,2519],{"className":2520,"style":2243},[2242],[83,2522,229],{"className":2523},[2247],[83,2525],{"className":2526,"style":2243},[2242],[83,2528,2530,2533,2573,2576,2579],{"className":2529},[2225],[83,2531],{"className":2532,"style":2257},[2229],[83,2534,2536,2539],{"className":2535},[2234],[83,2537,2180],{"className":2538,"style":2265},[2234,2264],[83,2540,2542],{"className":2541},[2269],[83,2543,2545,2565],{"className":2544},[2273,2274],[83,2546,2548,2562],{"className":2547},[2278],[83,2549,2551],{"className":2550,"style":2283},[2282],[83,2552,2553,2556],{"style":2286},[83,2554],{"className":2555,"style":2291},[2290],[83,2557,2559],{"className":2558},[2295,2296,2297,2298],[83,2560,411],{"className":2561},[2234,2298],[83,2563,2306],{"className":2564},[2305],[83,2566,2568],{"className":2567},[2278],[83,2569,2571],{"className":2570,"style":2313},[2282],[83,2572],{},[83,2574],{"className":2575,"style":2319},[2242],[83,2577,2186],{"className":2578},[2323],[83,2580],{"className":2581,"style":2319},[2242],[83,2583,2585,2588,2628,2631,2634],{"className":2584},[2225],[83,2586],{"className":2587,"style":2257},[2229],[83,2589,2591,2594],{"className":2590},[2234],[83,2592,2180],{"className":2593,"style":2265},[2234,2264],[83,2595,2597],{"className":2596},[2269],[83,2598,2600,2620],{"className":2599},[2273,2274],[83,2601,2603,2617],{"className":2602},[2278],[83,2604,2606],{"className":2605,"style":2283},[2282],[83,2607,2608,2611],{"style":2286},[83,2609],{"className":2610,"style":2291},[2290],[83,2612,2614],{"className":2613},[2295,2296,2297,2298],[83,2615,1161],{"className":2616},[2234,2298],[83,2618,2306],{"className":2619},[2305],[83,2621,2623],{"className":2622},[2278],[83,2624,2626],{"className":2625,"style":2313},[2282],[83,2627],{},[83,2629],{"className":2630,"style":2319},[2242],[83,2632,2195],{"className":2633},[2323],[83,2635],{"className":2636,"style":2319},[2242],[83,2638,2640,2644,2684,2687,2690],{"className":2639},[2225],[83,2641],{"className":2642,"style":2643},[2229],"height:0.7778em;vertical-align:-0.0833em;",[83,2645,2647,2650,2681],{"className":2646},[2234,2235],[83,2648,2200],{"className":2649},[2234],[83,2651,2653],{"className":2652},[2234,2398],[83,2654,2656],{"className":2655},[2273],[83,2657,2659],{"className":2658},[2278],[83,2660,2662,2670],{"className":2661,"style":2388},[2282],[83,2663,2664,2667],{"style":2410},[83,2665],{"className":2666,"style":2414},[2290],[83,2668,2207],{"className":2669},[2234],[83,2671,2672,2675],{"style":2410},[83,2673],{"className":2674,"style":2414},[2290],[83,2676,2678],{"className":2677,"style":2427},[2426],[83,2679,2210],{"className":2680},[2234],[83,2682,313],{"className":2683},[2234],[83,2685],{"className":2686,"style":2319},[2242],[83,2688,2186],{"className":2689},[2323],[83,2691],{"className":2692,"style":2319},[2242],[83,2694,2696,2699,2739,2742,2745],{"className":2695},[2225],[83,2697],{"className":2698,"style":2257},[2229],[83,2700,2702,2705],{"className":2701},[2234],[83,2703,2180],{"className":2704,"style":2265},[2234,2264],[83,2706,2708],{"className":2707},[2269],[83,2709,2711,2731],{"className":2710},[2273,2274],[83,2712,2714,2728],{"className":2713},[2278],[83,2715,2717],{"className":2716,"style":2283},[2282],[83,2718,2719,2722],{"style":2286},[83,2720],{"className":2721,"style":2291},[2290],[83,2723,2725],{"className":2724},[2295,2296,2297,2298],[83,2726,1149],{"className":2727},[2234,2298],[83,2729,2306],{"className":2730},[2305],[83,2732,2734],{"className":2733},[2278],[83,2735,2737],{"className":2736,"style":2313},[2282],[83,2738],{},[83,2740],{"className":2741,"style":2319},[2242],[83,2743,2195],{"className":2744},[2323],[83,2746],{"className":2747,"style":2319},[2242],[83,2749,2751,2754],{"className":2750},[2225],[83,2752],{"className":2753,"style":2388},[2229],[83,2755,2757],{"className":2756},[2234,2235],[83,2758,2499],{"className":2759},[2234],[12,2761,2762],{},"El modelo podrá:",[1359,2764,2765,2768,2771],{},[1362,2766,2767],{},"Ajustar diferentes interceptos por clima (por ejemplo, un término extra para días lluviosos).",[1362,2769,2770],{},"Mejorar precisión (ya que nos permite capturar esa variabilidad adicional).",[1362,2772,2773],{},"Reducir varianza del error (porque la varianza, es decir, la dispersión de los puntos alrededor de la línea de regresión, se reduce al explicar más factores).",[12,2775,2776,2780],{},[1882,2777],{"alt":2778,"src":2779},"Matriz de Correlación Cafetería","\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis\u002Fshared\u002Fcafeteria_correlation_matrix.webp",[1887,2781,2782],{},"Heatmap de Correlación",[12,2784,2785],{},"Vamos a descomponer la matriz de correlación, interpretando cada valor, pero antes recordemos qué significa cada número:",[1359,2787,2788,2794,2800],{},[1362,2789,2790,2793],{},[40,2791,2792],{},"1.00",": correlación positiva perfecta",[1362,2795,2796,2799],{},[40,2797,2798],{},"0.00",": no hay relación lineal",[1362,2801,2802,2805],{},[40,2803,2804],{},"-1.00",": correlación negativa perfecta",[12,2807,2808,2809,2812],{},"La matriz es ",[40,2810,2811],{},"simétrica",", es decir:",[74,2814,2818],{"className":2815,"code":2817,"language":2235},[2816],"language-text","Corr(A, B) = Corr(B, A)\n",[61,2819,2817],{"__ignoreMap":79},[12,2821,2822],{},"Por eso verás los mismos valores reflejados arriba y abajo de la diagonal.",[12,2824,2825,2826,2828],{},"La diagonal principal siempre es ",[40,2827,2792],{},", porque cada variable está perfectamente correlacionada consigo misma.",[12,2830,2831],{},"Las variables incluidas son:",[1359,2833,2834,2839,2844,2849,2854],{},[1362,2835,2836],{},[61,2837,2838],{},"temperature_c",[1362,2840,2841],{},[61,2842,2843],{},"ad_investment",[1362,2845,2846],{},[61,2847,2848],{},"local_event",[1362,2850,2851],{},[61,2852,2853],{},"discount",[1362,2855,2856],{},[61,2857,2858],{},"daily_sales",[1406,2860,2861],{},[1362,2862,2863,2865],{},[61,2864,2838],{},": Temperatura en grados Celsius.",[1359,2867,2868,2874,2881,2888,2895],{},[1362,2869,2870,2871,2873],{},"temperature_c - temperature_c = ",[40,2872,2792],{},"\nPerfecta correlación consigo misma.",[1362,2875,2876,2877,2880],{},"temperature_c - ad_investment = ",[40,2878,2879],{},"-0.03","\nRelación prácticamente inexistente.\nLa temperatura no influye en cuánto se invierte en publicidad.",[1362,2882,2883,2884,2887],{},"temperature_c - local_event = ",[40,2885,2886],{},"0.05","\nCorrelación muy débil positiva.\nLos eventos locales no dependen realmente del clima en este dataset.",[1362,2889,2890,2891,2894],{},"temperature_c - discount = ",[40,2892,2893],{},"0.04","\nSin relación relevante.\nLos descuentos no parecen aplicarse según temperatura.",[1362,2896,2897,2898,2901,2902,2905,2906,2914,2916],{},"temperature_c - daily_sales = ",[40,2899,2900],{},"-0.24","\nCorrelación negativa débil-moderada.\nCuando la temperatura aumenta, las ventas tienden a bajar ligeramente.",[2903,2904],"br",{},"Esto puede indicar:",[1359,2907,2908,2911],{},[1362,2909,2910],{},"El negocio vende productos que se consumen más en clima fresco.",[1362,2912,2913],{},"En días muy calurosos hay menos afluencia.",[2903,2915],{},"No es una relación fuerte, pero sí consistente.",[1406,2918,2919],{"start":103},[1362,2920,2921,2923],{},[61,2922,2843],{},": Inversión en publicidad.",[1359,2925,2926,2931,2938,2944],{},[1362,2927,2928,2929],{},"ad_investment - ad_investment = ",[40,2930,2792],{},[1362,2932,2933,2934,2937],{},"ad_investment - local_event = ",[40,2935,2936],{},"-0.05","\nPrácticamente independencia.\nLa inversión publicitaria no depende directamente de si hay evento.",[1362,2939,2940,2941,2943],{},"ad_investment - discount = ",[40,2942,2879],{},"\nSin relación.\nInversión y descuentos parecen decisiones separadas.",[1362,2945,2946,2947,2950,2951,2953,2954,2965,2967],{},"ad_investment - daily_sales = ",[40,2948,2949],{},"0.47","\nCorrelación positiva moderada.",[2903,2952],{},"Esto significa:",[1359,2955,2956,2959,2962],{},[1362,2957,2958],{},"A mayor inversión, mayores ventas.",[1362,2960,2961],{},"La relación es significativa, pero no perfecta.",[1362,2963,2964],{},"Hay otros factores influyendo.",[2903,2966],{},"Estadísticamente, es un predictor importante.",[1406,2969,2970],{"start":116},[1362,2971,2972,2974],{},[61,2973,2848],{},": Evento local.",[1359,2976,2977,2982,2989],{},[1362,2978,2979,2980],{},"local_event - local_event = ",[40,2981,2792],{},[1362,2983,2984,2985,2988],{},"local_event - discount = ",[40,2986,2987],{},"-0.06","\nRelación casi nula.\nNo parece que los eventos impliquen necesariamente descuentos.",[1362,2990,2991,2992,2995,2996,2998,2999,3010,3012],{},"local_event - daily_sales = ",[40,2993,2994],{},"0.57","\nEs la correlación más alta con ventas.",[2903,2997],{},"Interpretación:",[1359,3000,3001,3004,3007],{},[1362,3002,3003],{},"Cuando hay evento local, las ventas aumentan notablemente.",[1362,3005,3006],{},"Es el factor más influyente del dataset.",[1362,3008,3009],{},"Representa una variable clave para el modelo.",[2903,3011],{},"En términos prácticos:\nLos eventos generan tráfico o demanda adicional.",[1406,3014,3015],{"start":124},[1362,3016,3017,3019],{},[61,3018,2853],{},": Descuento.",[1359,3021,3022,3027],{},[1362,3023,3024,3025],{},"discount - discount = ",[40,3026,2792],{},[1362,3028,3029,3030,3033,3034,3036,3037,3045,3047,3048],{},"discount - daily_sales = ",[40,3031,3032],{},"0.13","\nCorrelación positiva débil.",[2903,3035],{},"Significa:",[1359,3038,3039,3042],{},[1362,3040,3041],{},"Los descuentos tienen un impacto pequeño.",[1362,3043,3044],{},"No parecen ser el motor principal de ventas.",[2903,3046],{},"Posibles explicaciones:",[1359,3049,3050,3053,3056],{},[1362,3051,3052],{},"Descuentos bajos",[1362,3054,3055],{},"Mala estrategia",[1362,3057,3058],{},"O efecto condicionado a otras variables",[1406,3060,3061],{"start":144},[1362,3062,3063,3065],{},[61,3064,2858],{},": Ventas diarias.",[12,3067,3068],{},"Ya interpretamos todas sus correlaciones con las demás variables:",[3070,3071,3072,3085],"table",{},[3073,3074,3075],"thead",{},[3076,3077,3078,3082],"tr",{},[3079,3080,3081],"th",{},"Variable",[3079,3083,3084],{},"Correlación",[3086,3087,3088,3095,3101,3107],"tbody",{},[3076,3089,3090,3093],{},[3091,3092,2838],"td",{},[3091,3094,2900],{},[3076,3096,3097,3099],{},[3091,3098,2843],{},[3091,3100,2949],{},[3076,3102,3103,3105],{},[3091,3104,2848],{},[3091,3106,2994],{},[3076,3108,3109,3111],{},[3091,3110,2853],{},[3091,3112,3032],{},[12,3114,3115],{},"Ordenadas por impacto lineal:",[1406,3117,3118,3121,3124,3127],{},[1362,3119,3120],{},"local_event (0.57)",[1362,3122,3123],{},"ad_investment (0.47)",[1362,3125,3126],{},"temperature_c (-0.24)",[1362,3128,3129],{},"discount (0.13)",[12,3131,3132],{},[40,3133,3134],{},"¿Qué nos dice esto a nivel de modelado?",[12,3136,3137],{},"Lo primero es que las variables más predictivas para estimar ventas son:",[1359,3139,3140,3142],{},[1362,3141,2848],{},[1362,3143,2843],{},[12,3145,3146],{},"Ambas deberían incluirse en el modelo.",[12,3148,3149],{},"Luego tenemos la multicolinealidad",[12,3151,3152],{},"Observamos que:",[1359,3154,3155,3158],{},[1362,3156,3157],{},"Ninguna variable independiente tiene correlación alta con otra.",[1362,3159,3160],{},"Todos los valores entre predictores están cerca de 0.",[12,3162,3163],{},"Esto es excelente porque significa que no hay redundancia fuerte y que cada variable aporta información distinta.",[12,3165,3166],{},"Si tuviesemos valores cercanos a 1 o -1 entre predictores (por ejemplo, ad_investment y local_event), tendríamos que considerar eliminar o combinar variables para evitar problemas de multicolinealidad.",[12,3168,3169],{},"Asi que con todo esto podemos concluir:",[1359,3171,3172,3175,3178,3181,3184,3187],{},[1362,3173,3174],{},"El principal motor de ventas son los eventos locales.",[1362,3176,3177],{},"La inversión publicitaria tiene un impacto claro y consistente.",[1362,3179,3180],{},"La temperatura afecta ligeramente de forma negativa.",[1362,3182,3183],{},"Los descuentos tienen impacto bajo.",[1362,3185,3186],{},"No hay multicolinealidad problemática.",[1362,3188,3189],{},"El dataset es apto para un modelo de regresión múltiple.",[2073,3191,3192,3195],{},[12,3193,3194],{},"Con esta información, un gerente de la cafetería podría tomar decisiones estratégicas como:",[1359,3196,3197,3200,3203,3206],{},[1362,3198,3199],{},"Prioriza campañas durante eventos locales.",[1362,3201,3202],{},"Mantén inversión publicitaria constante.",[1362,3204,3205],{},"Reevaluar estrategia de descuentos.",[1362,3207,3208],{},"Considerar estrategias específicas para días calurosos.",[53,3210,3212],{"id":3211},"paso-4-de-los-datos-a-la-predicción-modelado","Paso 4: De los Datos a la Predicción (Modelado)",[12,3214,3215,3216,133],{},"Con el EDA completado, transformamos el clima a un formato binario y alimentamos a un modelo de ",[1887,3217,3218],{},"Regresión Lineal Simple",[74,3220,3222],{"className":76,"code":3221,"language":78,"meta":79,"style":79},"from sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n\n# One-Hot Encoding: Convierte \"Soleado\" o \"Lluvioso\" en columnas de 0s y 1s\ndf_encoded = pd.get_dummies(df, columns=[\"clima\"])\nX = df_encoded.drop(\"ventas_diarias\", axis=1)\ny = df_encoded[\"ventas_diarias\"]\n\n# Dividimos: 80% para que el modelo aprenda, 20% para examinarlo después\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n\nmodelo_cafeteria = LinearRegression()\nmodelo_cafeteria.fit(X_train, y_train)\n\n# Hacemos predicciones con el modelo entrenado\npredicciones = modelo_cafeteria.predict(X_test)\n",[61,3223,3224,3242,3258,3284,3288,3293,3326,3360,3379,3383,3388,3443,3447,3459,3479,3483,3488],{"__ignoreMap":79},[83,3225,3226,3229,3232,3234,3237,3239],{"class":85,"line":86},[83,3227,3228],{"class":89},"from",[83,3230,3231],{"class":93}," sklearn",[83,3233,133],{"class":132},[83,3235,3236],{"class":93},"model_selection ",[83,3238,90],{"class":89},[83,3240,3241],{"class":93}," train_test_split\n",[83,3243,3244,3246,3248,3250,3253,3255],{"class":85,"line":103},[83,3245,3228],{"class":89},[83,3247,3231],{"class":93},[83,3249,133],{"class":132},[83,3251,3252],{"class":93},"linear_model ",[83,3254,90],{"class":89},[83,3256,3257],{"class":93}," LinearRegression\n",[83,3259,3260,3262,3264,3266,3269,3271,3274,3276,3279,3281],{"class":85,"line":116},[83,3261,3228],{"class":89},[83,3263,3231],{"class":93},[83,3265,133],{"class":132},[83,3267,3268],{"class":93},"metrics ",[83,3270,90],{"class":89},[83,3272,3273],{"class":93}," mean_absolute_error",[83,3275,256],{"class":132},[83,3277,3278],{"class":93}," mean_squared_error",[83,3280,256],{"class":132},[83,3282,3283],{"class":93}," r2_score\n",[83,3285,3286],{"class":85,"line":124},[83,3287,161],{"emptyLinePlaceholder":160},[83,3289,3290],{"class":85,"line":144},[83,3291,3292],{"class":167},"# One-Hot Encoding: Convierte \"Soleado\" o \"Lluvioso\" en columnas de 0s y 1s\n",[83,3294,3295,3298,3300,3302,3304,3307,3309,3311,3313,3315,3318,3320,3322,3324],{"class":85,"line":157},[83,3296,3297],{"class":93},"df_encoded ",[83,3299,229],{"class":132},[83,3301,837],{"class":93},[83,3303,133],{"class":132},[83,3305,3306],{"class":93},"get_dummies",[83,3308,187],{"class":132},[83,3310,866],{"class":93},[83,3312,256],{"class":132},[83,3314,853],{"class":852},[83,3316,3317],{"class":132},"=[",[83,3319,247],{"class":246},[83,3321,813],{"class":250},[83,3323,247],{"class":246},[83,3325,418],{"class":132},[83,3327,3328,3331,3333,3336,3338,3341,3343,3345,3347,3349,3351,3354,3356,3358],{"class":85,"line":164},[83,3329,3330],{"class":93},"X ",[83,3332,229],{"class":132},[83,3334,3335],{"class":93}," df_encoded",[83,3337,133],{"class":132},[83,3339,3340],{"class":93},"drop",[83,3342,187],{"class":132},[83,3344,247],{"class":246},[83,3346,822],{"class":250},[83,3348,247],{"class":246},[83,3350,256],{"class":132},[83,3352,3353],{"class":852}," axis",[83,3355,229],{"class":132},[83,3357,1161],{"class":190},[83,3359,194],{"class":132},[83,3361,3362,3365,3367,3369,3371,3373,3375,3377],{"class":85,"line":171},[83,3363,3364],{"class":93},"y ",[83,3366,229],{"class":132},[83,3368,3335],{"class":93},[83,3370,1481],{"class":132},[83,3372,247],{"class":246},[83,3374,822],{"class":250},[83,3376,247],{"class":246},[83,3378,276],{"class":132},[83,3380,3381],{"class":85,"line":197},[83,3382,161],{"emptyLinePlaceholder":160},[83,3384,3385],{"class":85,"line":212},[83,3386,3387],{"class":167},"# Dividimos: 80% para que el modelo aprenda, 20% para examinarlo después\n",[83,3389,3390,3393,3395,3398,3400,3403,3405,3408,3410,3413,3415,3418,3420,3422,3424,3427,3429,3432,3434,3437,3439,3441],{"class":85,"line":217},[83,3391,3392],{"class":93},"X_train",[83,3394,256],{"class":132},[83,3396,3397],{"class":93}," X_test",[83,3399,256],{"class":132},[83,3401,3402],{"class":93}," y_train",[83,3404,256],{"class":132},[83,3406,3407],{"class":93}," y_test ",[83,3409,229],{"class":132},[83,3411,3412],{"class":93}," train_test_split",[83,3414,187],{"class":132},[83,3416,3417],{"class":93},"X",[83,3419,256],{"class":132},[83,3421,1653],{"class":93},[83,3423,256],{"class":132},[83,3425,3426],{"class":852}," test_size",[83,3428,229],{"class":132},[83,3430,3431],{"class":190},"0.2",[83,3433,256],{"class":132},[83,3435,3436],{"class":852}," random_state",[83,3438,229],{"class":132},[83,3440,191],{"class":190},[83,3442,194],{"class":132},[83,3444,3445],{"class":85,"line":223},[83,3446,161],{"emptyLinePlaceholder":160},[83,3448,3449,3452,3454,3457],{"class":85,"line":235},[83,3450,3451],{"class":93},"modelo_cafeteria ",[83,3453,229],{"class":132},[83,3455,3456],{"class":93}," LinearRegression",[83,3458,874],{"class":132},[83,3460,3461,3464,3466,3469,3471,3473,3475,3477],{"class":85,"line":279},[83,3462,3463],{"class":93},"modelo_cafeteria",[83,3465,133],{"class":132},[83,3467,3468],{"class":93},"fit",[83,3470,187],{"class":132},[83,3472,3392],{"class":93},[83,3474,256],{"class":132},[83,3476,3402],{"class":93},[83,3478,194],{"class":132},[83,3480,3481],{"class":85,"line":290},[83,3482,161],{"emptyLinePlaceholder":160},[83,3484,3485],{"class":85,"line":295},[83,3486,3487],{"class":167},"# Hacemos predicciones con el modelo entrenado\n",[83,3489,3490,3493,3495,3498,3500,3503,3505,3508],{"class":85,"line":319},[83,3491,3492],{"class":93},"predicciones ",[83,3494,229],{"class":132},[83,3496,3497],{"class":93}," modelo_cafeteria",[83,3499,133],{"class":132},[83,3501,3502],{"class":93},"predict",[83,3504,187],{"class":132},[83,3506,3507],{"class":93},"X_test",[83,3509,194],{"class":132},[53,3511,3513],{"id":3512},"paso-5-calificando-al-modelo","Paso 5: Calificando al Modelo",[12,3515,3516],{},"Ahora evaluemos que tan \"certero\" es nuestro algoritmo comparando las ventas contra sus predicciones.",[74,3518,3520],{"className":76,"code":3519,"language":78,"meta":79,"style":79},"mae = mean_absolute_error(y_test, predicciones)\nrmse = np.sqrt(mean_squared_error(y_test, predicciones))\nr2 = r2_score(y_test, predicciones)\n\nprint(f\"MAE: ${mae:.2f}\")\nprint(f\"RMSE: ${rmse:.2f}\")\nprint(f\"R^2: {r2:.2f}\")\n",[61,3521,3522,3543,3572,3592,3596,3624,3648],{"__ignoreMap":79},[83,3523,3524,3527,3529,3531,3533,3536,3538,3541],{"class":85,"line":86},[83,3525,3526],{"class":93},"mae ",[83,3528,229],{"class":132},[83,3530,3273],{"class":93},[83,3532,187],{"class":132},[83,3534,3535],{"class":93},"y_test",[83,3537,256],{"class":132},[83,3539,3540],{"class":93}," predicciones",[83,3542,194],{"class":132},[83,3544,3545,3548,3550,3552,3554,3557,3559,3562,3564,3566,3568,3570],{"class":85,"line":103},[83,3546,3547],{"class":93},"rmse ",[83,3549,229],{"class":132},[83,3551,680],{"class":93},[83,3553,133],{"class":132},[83,3555,3556],{"class":93},"sqrt",[83,3558,187],{"class":132},[83,3560,3561],{"class":93},"mean_squared_error",[83,3563,187],{"class":132},[83,3565,3535],{"class":93},[83,3567,256],{"class":132},[83,3569,3540],{"class":93},[83,3571,1464],{"class":132},[83,3573,3574,3577,3579,3582,3584,3586,3588,3590],{"class":85,"line":116},[83,3575,3576],{"class":93},"r2 ",[83,3578,229],{"class":132},[83,3580,3581],{"class":93}," r2_score",[83,3583,187],{"class":132},[83,3585,3535],{"class":93},[83,3587,256],{"class":132},[83,3589,3540],{"class":93},[83,3591,194],{"class":132},[83,3593,3594],{"class":85,"line":124},[83,3595,161],{"emptyLinePlaceholder":160},[83,3597,3598,3600,3602,3605,3608,3611,3614,3617,3620,3622],{"class":85,"line":144},[83,3599,904],{"class":307},[83,3601,187],{"class":132},[83,3603,3604],{"class":512},"f",[83,3606,3607],{"class":250},"\"MAE: $",[83,3609,3610],{"class":1020},"{",[83,3612,3613],{"class":93},"mae",[83,3615,3616],{"class":512},":.2f",[83,3618,3619],{"class":1020},"}",[83,3621,247],{"class":250},[83,3623,194],{"class":132},[83,3625,3626,3628,3630,3632,3635,3637,3640,3642,3644,3646],{"class":85,"line":157},[83,3627,904],{"class":307},[83,3629,187],{"class":132},[83,3631,3604],{"class":512},[83,3633,3634],{"class":250},"\"RMSE: $",[83,3636,3610],{"class":1020},[83,3638,3639],{"class":93},"rmse",[83,3641,3616],{"class":512},[83,3643,3619],{"class":1020},[83,3645,247],{"class":250},[83,3647,194],{"class":132},[83,3649,3650,3652,3654,3656,3659,3661,3664,3666,3668,3670],{"class":85,"line":164},[83,3651,904],{"class":307},[83,3653,187],{"class":132},[83,3655,3604],{"class":512},[83,3657,3658],{"class":250},"\"R^2: ",[83,3660,3610],{"class":1020},[83,3662,3663],{"class":93},"r2",[83,3665,3616],{"class":512},[83,3667,3619],{"class":1020},[83,3669,247],{"class":250},[83,3671,194],{"class":132},[12,3673,3674],{},"Dando como resultado:",[12,3676,3677,3678],{},"MAE: ",[61,3679,3680],{},"$55.39",[12,3682,3683,3684],{},"RMSE: ",[61,3685,3686],{},"$74.51",[12,3688,3689,3753],{},[83,3690,3692,3712],{"className":3691},[2151],[83,3693,3695],{"className":3694},[2155],[2157,3696,3697],{"xmlns":2159},[2162,3698,3699,3709],{},[2165,3700,3701],{},[3702,3703,3704,3707],"msup",{},[2178,3705,3706],{},"R",[2182,3708,1149],{},[2214,3710,3711],{"encoding":2216},"R^2",[83,3713,3715],{"className":3714,"ariaHidden":2204},[2221],[83,3716,3718,3722],{"className":3717},[2225],[83,3719],{"className":3720,"style":3721},[2229],"height:0.8141em;",[83,3723,3725,3729],{"className":3724},[2234],[83,3726,3706],{"className":3727,"style":3728},[2234,2264],"margin-right:0.0077em;",[83,3730,3732],{"className":3731},[2269],[83,3733,3735],{"className":3734},[2273],[83,3736,3738],{"className":3737},[2278],[83,3739,3741],{"className":3740,"style":3721},[2282],[83,3742,3744,3747],{"style":3743},"top:-3.063em;margin-right:0.05em;",[83,3745],{"className":3746,"style":2291},[2290],[83,3748,3750],{"className":3749},[2295,2296,2297,2298],[83,3751,1149],{"className":3752},[2234,2298],": 0.88",[12,3755,3756],{},"¿Qué significan estos números?",[1359,3758,3759,3768,3777],{},[1362,3760,3761,3764,3765,3767],{},[40,3762,3763],{},"MAE (Error Absoluto Medio)",": En promedio, nuestras predicciones se desvían de las ventas reales por aproximadamente ",[61,3766,3680],{},". Esto nos da una idea de la magnitud del error en términos monetarios.",[1362,3769,3770,3773,3774,3776],{},[40,3771,3772],{},"RMSE (Error Cuadrático Medio)",": Al penalizar más los errores grandeses, el RMSE de ",[61,3775,3686],{}," indica que, aunque la mayoría de las predicciones están cerca, hay algunos casos donde el modelo se equivoca más significativamente.",[1362,3778,3779,3840,3841,3899],{},[40,3780,3781,3839],{},[83,3782,3784,3801],{"className":3783},[2151],[83,3785,3787],{"className":3786},[2155],[2157,3788,3789],{"xmlns":2159},[2162,3790,3791,3799],{},[2165,3792,3793],{},[3702,3794,3795,3797],{},[2178,3796,3706],{},[2182,3798,1149],{},[2214,3800,3711],{"encoding":2216},[83,3802,3804],{"className":3803,"ariaHidden":2204},[2221],[83,3805,3807,3810],{"className":3806},[2225],[83,3808],{"className":3809,"style":3721},[2229],[83,3811,3813,3816],{"className":3812},[2234],[83,3814,3706],{"className":3815,"style":3728},[2234,2264],[83,3817,3819],{"className":3818},[2269],[83,3820,3822],{"className":3821},[2273],[83,3823,3825],{"className":3824},[2278],[83,3826,3828],{"className":3827,"style":3721},[2282],[83,3829,3830,3833],{"style":3743},[83,3831],{"className":3832,"style":2291},[2290],[83,3834,3836],{"className":3835},[2295,2296,2297,2298],[83,3837,1149],{"className":3838},[2234,2298]," (Puntuación de Determinación)",": Un ",[83,3842,3844,3861],{"className":3843},[2151],[83,3845,3847],{"className":3846},[2155],[2157,3848,3849],{"xmlns":2159},[2162,3850,3851,3859],{},[2165,3852,3853],{},[3702,3854,3855,3857],{},[2178,3856,3706],{},[2182,3858,1149],{},[2214,3860,3711],{"encoding":2216},[83,3862,3864],{"className":3863,"ariaHidden":2204},[2221],[83,3865,3867,3870],{"className":3866},[2225],[83,3868],{"className":3869,"style":3721},[2229],[83,3871,3873,3876],{"className":3872},[2234],[83,3874,3706],{"className":3875,"style":3728},[2234,2264],[83,3877,3879],{"className":3878},[2269],[83,3880,3882],{"className":3881},[2273],[83,3883,3885],{"className":3884},[2278],[83,3886,3888],{"className":3887,"style":3721},[2282],[83,3889,3890,3893],{"style":3743},[83,3891],{"className":3892,"style":2291},[2290],[83,3894,3896],{"className":3895},[2295,2296,2297,2298],[83,3897,1149],{"className":3898},[2234,2298]," de 0.88 significa que el modelo explica el 88% de la variabilidad en las ventas diarias. Esto es un resultado bastante bueno, indicando que el modelo captura la mayoría de los patrones presentes en los datos.",[12,3901,3902],{},[40,3903,3904],{},"Grafico de Predicciones vs Realidad",[74,3906,3908],{"className":76,"code":3907,"language":78,"meta":79,"style":79},"plt.figure(figsize=(8,5))\nsns.scatterplot(x=y_test, y=predictions)\nplt.plot([y.min(), y.max()], [y.min(), y.max()], 'r--')  # Perfect reference line\nplt.title(\"Predictions vs Actual Sales\")\nplt.xlabel(\"Actual Sales ($)\")\nplt.ylabel(\"Model Predictions ($)\")\nplt.show()\n",[61,3909,3910,3932,3959,4020,4039,4058,4077],{"__ignoreMap":79},[83,3911,3912,3914,3916,3918,3920,3922,3924,3926,3928,3930],{"class":85,"line":86},[83,3913,1440],{"class":93},[83,3915,133],{"class":132},[83,3917,1445],{"class":93},[83,3919,187],{"class":132},[83,3921,1450],{"class":852},[83,3923,1453],{"class":132},[83,3925,1456],{"class":190},[83,3927,256],{"class":132},[83,3929,1461],{"class":190},[83,3931,1464],{"class":132},[83,3933,3934,3936,3938,3940,3942,3944,3946,3948,3950,3952,3954,3957],{"class":85,"line":103},[83,3935,1469],{"class":93},[83,3937,133],{"class":132},[83,3939,1635],{"class":93},[83,3941,187],{"class":132},[83,3943,1640],{"class":852},[83,3945,229],{"class":132},[83,3947,3535],{"class":93},[83,3949,256],{"class":132},[83,3951,1653],{"class":852},[83,3953,229],{"class":132},[83,3955,3956],{"class":93},"predictions",[83,3958,194],{"class":132},[83,3960,3961,3963,3965,3968,3970,3973,3975,3977,3980,3982,3984,3986,3989,3991,3993,3995,3997,3999,4001,4003,4005,4007,4010,4013,4015,4017],{"class":85,"line":116},[83,3962,1440],{"class":93},[83,3964,133],{"class":132},[83,3966,3967],{"class":93},"plot",[83,3969,408],{"class":132},[83,3971,3972],{"class":93},"y",[83,3974,133],{"class":132},[83,3976,1263],{"class":93},[83,3978,3979],{"class":132},"(),",[83,3981,1653],{"class":93},[83,3983,133],{"class":132},[83,3985,1341],{"class":93},[83,3987,3988],{"class":132},"()],",[83,3990,243],{"class":132},[83,3992,3972],{"class":93},[83,3994,133],{"class":132},[83,3996,1263],{"class":93},[83,3998,3979],{"class":132},[83,4000,1653],{"class":93},[83,4002,133],{"class":132},[83,4004,1341],{"class":93},[83,4006,3988],{"class":132},[83,4008,4009],{"class":246}," '",[83,4011,4012],{"class":250},"r--",[83,4014,961],{"class":246},[83,4016,534],{"class":132},[83,4018,4019],{"class":167},"  # Perfect reference line\n",[83,4021,4022,4024,4026,4028,4030,4032,4035,4037],{"class":85,"line":124},[83,4023,1440],{"class":93},[83,4025,133],{"class":132},[83,4027,1533],{"class":93},[83,4029,187],{"class":132},[83,4031,247],{"class":246},[83,4033,4034],{"class":250},"Predictions vs Actual Sales",[83,4036,247],{"class":246},[83,4038,194],{"class":132},[83,4040,4041,4043,4045,4047,4049,4051,4054,4056],{"class":85,"line":144},[83,4042,1440],{"class":93},[83,4044,133],{"class":132},[83,4046,1553],{"class":93},[83,4048,187],{"class":132},[83,4050,247],{"class":246},[83,4052,4053],{"class":250},"Actual Sales ($)",[83,4055,247],{"class":246},[83,4057,194],{"class":132},[83,4059,4060,4062,4064,4066,4068,4070,4073,4075],{"class":85,"line":157},[83,4061,1440],{"class":93},[83,4063,133],{"class":132},[83,4065,1573],{"class":93},[83,4067,187],{"class":132},[83,4069,247],{"class":246},[83,4071,4072],{"class":250},"Model Predictions ($)",[83,4074,247],{"class":246},[83,4076,194],{"class":132},[83,4078,4079,4081,4083,4085],{"class":85,"line":164},[83,4080,1440],{"class":93},[83,4082,133],{"class":132},[83,4084,1593],{"class":93},[83,4086,874],{"class":132},[12,4088,4089,4093],{},[1882,4090],{"alt":4091,"src":4092},"Predicciones vs Realidad","\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis\u002Fshared\u002Fpredictions_vs_actual_sales.webp",[1887,4094,4095],{},"Gráfico de Predicciones vs Ventas Reales",[12,4097,4098],{},"Como se observa, tenemos una línea de referencia (en rojo) que representa la perfección: si todas las ventas estuvieran exactamente en esa línea, el modelo sería perfecto, pero la realidad nunca será asi de ideal. Aún así, la mayoría de los puntos se agrupan alrededor de esa línea, lo que indica que el modelo tiene un buen desempeño general. Algunos puntos se alejan más, lo que refleja los casos donde el modelo no predice tan bien, posiblemente debido a factores no capturados en el dataset o a la variabilidad inherente en las ventas diarias.",[12,4100,4101],{},"Podemos también obtener los coeficientes del modelo para entender la importancia de cada variable:",[74,4103,4105],{"className":76,"code":4104,"language":78,"meta":79,"style":79},"coeficientes = pd.DataFrame({\n    'Variable': X.columns,\n    'Coeficiente': modelo_cafeteria.coef_\n})\ndisplay(coeficientes.sort_values(by='Coeficiente', ascending=False))\n",[61,4106,4107,4123,4144,4162,4167],{"__ignoreMap":79},[83,4108,4109,4112,4114,4116,4118,4120],{"class":85,"line":86},[83,4110,4111],{"class":93},"coeficientes ",[83,4113,229],{"class":132},[83,4115,837],{"class":93},[83,4117,133],{"class":132},[83,4119,842],{"class":93},[83,4121,4122],{"class":132},"({\n",[83,4124,4125,4128,4130,4132,4134,4137,4139,4141],{"class":85,"line":103},[83,4126,4127],{"class":246},"    '",[83,4129,3081],{"class":250},[83,4131,961],{"class":246},[83,4133,624],{"class":132},[83,4135,4136],{"class":93}," X",[83,4138,133],{"class":132},[83,4140,858],{"class":93},[83,4142,4143],{"class":132},",\n",[83,4145,4146,4148,4151,4153,4155,4157,4159],{"class":85,"line":116},[83,4147,4127],{"class":246},[83,4149,4150],{"class":250},"Coeficiente",[83,4152,961],{"class":246},[83,4154,624],{"class":132},[83,4156,3497],{"class":93},[83,4158,133],{"class":132},[83,4160,4161],{"class":93},"coef_\n",[83,4163,4164],{"class":85,"line":124},[83,4165,4166],{"class":132},"})\n",[83,4168,4169,4172,4174,4177,4179,4182,4184,4187,4189,4191,4193,4195,4197,4200,4202,4205],{"class":85,"line":144},[83,4170,4171],{"class":93},"display",[83,4173,187],{"class":132},[83,4175,4176],{"class":93},"coeficientes",[83,4178,133],{"class":132},[83,4180,4181],{"class":93},"sort_values",[83,4183,187],{"class":132},[83,4185,4186],{"class":852},"by",[83,4188,229],{"class":132},[83,4190,961],{"class":246},[83,4192,4150],{"class":250},[83,4194,961],{"class":246},[83,4196,256],{"class":132},[83,4198,4199],{"class":852}," ascending",[83,4201,229],{"class":132},[83,4203,4204],{"class":89},"False",[83,4206,1464],{"class":132},[12,4208,4209],{},"Esto nos arroja el siguiente resultado:",[3070,4211,4212,4222],{},[3073,4213,4214],{},[3076,4215,4216,4219],{},[3079,4217,4218],{},"Feature",[3079,4220,4221],{},"Coefficient",[3086,4223,4224,4231,4239,4246,4253,4260,4268],{},[3076,4225,4226,4228],{},[3091,4227,2848],{},[3091,4229,4230],{},"261.839739",[3076,4232,4233,4236],{},[3091,4234,4235],{},"weather_Rainy",[3091,4237,4238],{},"124.573377",[3076,4240,4241,4243],{},[3091,4242,2853],{},[3091,4244,4245],{},"4.837618",[3076,4247,4248,4250],{},[3091,4249,2843],{},[3091,4251,4252],{},"2.482678",[3076,4254,4255,4257],{},[3091,4256,2838],{},[3091,4258,4259],{},"-8.578684",[3076,4261,4262,4265],{},[3091,4263,4264],{},"weather_Cloudy",[3091,4266,4267],{},"-28.151991",[3076,4269,4270,4273],{},[3091,4271,4272],{},"weather_Sunny",[3091,4274,4275],{},"-96.421386",[12,4277,4278],{},"Lo que nos dice cada coeficiente es el impacto que tiene esa variable en las ventas diarias, manteniendo las demás constantes. Por ejemplo:",[1359,4280,4281,4287,4293,4300,4306,4312,4318],{},[1362,4282,4283,4284,133],{},"Un evento local (local_event) aumenta las ventas en aproximadamente ",[61,4285,4286],{},"$261.84",[1362,4288,4289,4290,133],{},"Un día lluvioso (weather_Rainy) aumenta las ventas en aproximadamente ",[61,4291,4292],{},"$124.57",[1362,4294,4295,4296,4299],{},"Un descuento (discount) aumenta las ventas en aproximadamente ",[61,4297,4298],{},"$4.84"," por cada punto porcentual de descuento.",[1362,4301,4302,4303,133],{},"Cada dólar adicional invertido en publicidad (ad_investment) aumenta las ventas en aproximadamente ",[61,4304,4305],{},"$2.48",[1362,4307,4308,4309],{},"Cada grado Celsius adicional (temperature_c) disminuye las ventas en aproximadamente ",[61,4310,4311],{},"$8.58",[1362,4313,4314,4315,133],{},"Un día nublado (weather_Cloudy) disminuye las ventas en aproximadamente ",[61,4316,4317],{},"$28.15",[1362,4319,4320,4321,133],{},"Un día soleado (weather_Sunny) disminuye las ventas en aproximadamente ",[61,4322,4323],{},"$96.42",[12,4325,4326],{},"¿Qué mejoras podemos hacer al modelo?",[1359,4328,4329,4346,4352,4361,4367],{},[1362,4330,4331,4334,4335,1966,4337,4339,4340,1966,4342,4345],{},[40,4332,4333],{},"Feature Engineering",": Explorar la creación de nuevas características a partir de las existentes. Por ejemplo, los términos de interacción entre ",[61,4336,2843],{},[61,4338,2853],{},", o ",[61,4341,2838],{},[61,4343,4344],{},"weather",", podrían capturar relaciones más complejas.",[1362,4347,4348,4351],{},[40,4349,4350],{},"Relaciones no lineales",": El modelo actual es lineal. Si los diagramas de dispersión sugieren relaciones no lineales (p. ej., ventas que alcanzan su máximo a cierta temperatura y luego disminuyen), las características polinómicas u otros modelos no lineales (como Random Forest o Gradient Boosting) podrían capturarlas mejor.",[1362,4353,4354,4357,4358,4360],{},[40,4355,4356],{},"Aspectos de series temporales",": Dado que los datos son de ventas diarias, podría haber patrones temporales (p. ej., efectos del día de la semana, estacionalidad no capturada completamente por ",[61,4359,4344],{},"). Incorporar características como el día de la semana, el mes o utilizar modelos específicos para series temporales podría ser beneficioso.",[1362,4362,4363,4366],{},[40,4364,4365],{},"Detección de valores atípicos",": Investigar cualquier valor atípico potencial en los datos que pueda estar influyendo desproporcionadamente en los coeficientes y predicciones del modelo.",[1362,4368,4369,4372],{},[40,4370,4371],{},"Más datos",": Si bien no siempre es factible, contar con puntos de datos más diversos (por ejemplo, de diferentes cafeterías, durante un período más prolongado y con condiciones más variadas) podría ayudar a que el modelo se generalice mejor.",[4374,4375,4376],"style",{},"html pre.shiki code .sTPum, html code.shiki .sTPum{--shiki-default:#1E754F;--shiki-dark:#4D9375}html pre.shiki code .s8w-G, html code.shiki .s8w-G{--shiki-default:#393A34;--shiki-dark:#DBD7CAEE}html pre.shiki code .si6no, html code.shiki .si6no{--shiki-default:#999999;--shiki-dark:#666666}html pre.shiki code 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.sfsYZ{--shiki-default:#A65E2B;--shiki-dark:#C99076}",{"title":79,"searchDepth":116,"depth":116,"links":4378},[4379],{"id":34,"depth":103,"text":35,"children":4380},[4381,4382,4383,4384,4385],{"id":55,"depth":116,"text":56},{"id":877,"depth":116,"text":878},{"id":1400,"depth":116,"text":1401},{"id":3211,"depth":116,"text":3212},{"id":3512,"depth":116,"text":3513},"2026-04-19","md","\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis\u002Fshared\u002Feda.webp",{},"\u002Fblog\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis",{"title":6,"description":14},{"loc":4393,"priority":4394,"lastmod":4386},"\u002Fes\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis",0.7,"experimenting-with-exploratory-data-analysis","blog\u002Fblog\u002Fexperimenting-with-exploratory-data-analysis","En este artículo, exploraremos el proceso de análisis exploratorio de datos (EDA) en el contexto de proyectos de aprendizaje automático.",[4399,4400,4401,4402,4403],"aprendizaje automático","análisis de datos","EDA","proyectos de machine learning","análisis exploratorio","jLuQVdubL3rr8PUSL6UI21aRoxNP9hjQ-h94ciQdHmc",{"id":4406,"title":24,"author":7,"body":4407,"date":6084,"description":4411,"extension":4387,"image":6085,"lastmod":6084,"meta":6086,"navigation":160,"order":124,"path":6087,"seo":6088,"sitemap":6089,"slug":6091,"stem":6092,"summary":6093,"tags":6094,"__hash__":6099},"content_es\u002Fblog\u002Fblog\u002Fworkflow-machine-learning-projects.md",{"type":9,"value":4408,"toc":6047},[4409,4412,4419,4421,4423,4426,4452,4466,4475,4477,4481,4484,4510,4513,4516,4538,4540,4544,4547,4573,4576,4580,4583,4586,4590,4593,4649,4652,4677,4682,4686,4715,4719,4722,4748,4751,4755,4811,4815,4823,4826,4832,4840,4846,4854,4860,4868,4872,4875,4901,4909,4915,4918,4922,4925,4964,4967,4971,4974,4991,4993,4999,5003,5028,5032,5035,5037,5051,5055,5058,5074,5077,5081,5084,5087,5090,5110,5115,5118,5156,5160,5163,5207,5211,5214,5256,5260,5263,5267,5270,5274,5277,5309,5313,5316,5336,5339,5377,5380,5412,5415,5441,5443,5447,5450,5455,5458,5483,5486,5492,5495,5501,5508,5514,5521,5525,5531,5534,5540,5545,5551,5557,5560,5567,5570,5576,5579,5583,5586,5593,5599,5606,5612,5616,5619,5625,5628,5634,5640,5644,5647,5654,5657,5663,5670,5673,5679,5686,5689,5695,5698,5701,5704,5749,5752,5758,5765,5769,5772,5783,5786,5845,5851,5862,5868,5872,5875,5886,5889,5892,5895,5898,5906,5909,5915,5918,5924,5927,5933,5936,5942,5945,5949,5952,5966,5969,5973,5976,5979,5982,5990,5997,6000,6003,6011,6013,6020,6031,6038,6045],[12,4410,4411],{},"Continuamos aprendiendo sobre el mundo del aprendizaje automático, y en esta ocasión, nos adentraremos en el flujo típico de un proyecto de aprendizaje automático.",[12,4413,17,4414],{},[19,4415,4418],{"href":4416,"rel":4417},"https:\u002F\u002Fderas.dev\u002Fes\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations",[23],"Paradigmas de aprendizaje automático y fundamentos matemáticos",[26,4420],{},[29,4422],{},[12,4424,4425],{},"¿Por qué es importante entender el flujo de un proyecto de aprendizaje automático?",[1359,4427,4428,4434,4440,4446],{},[1362,4429,4430,4433],{},[40,4431,4432],{},"El proceso es más importante que el resultado",": Los modelos exitosos no dependen únicamente de algoritmos sofisticados, sino de un\nproceso bien estructurado. Un Random Forest con datos limpios y bien preparados supera consistentemente a una red neuronal profunda con datos de mala calidad.",[1362,4435,4436,4439],{},[40,4437,4438],{},"Reproducibilidad",": Un flujo de trabajo claro y documentado permite que otros científicos de datos puedan reproducir tus resultados, lo cual es fundamental para la validación y el avance del conocimiento en el campo.",[1362,4441,4442,4445],{},[40,4443,4444],{},"Colaboración",": En proyectos de aprendizaje automático, a menudo hay múltiples personas involucradas, desde científicos de datos hasta ingenieros de datos y stakeholders. Un flujo de trabajo bien definido facilita la comunicación y la colaboración entre todos los miembros del equipo.",[1362,4447,4448,4451],{},[40,4449,4450],{},"Reduce el riesgo de errores",": Un proceso estructurado ayuda a identificar y corregir errores en las etapas tempranas del proyecto, lo que puede ahorrar tiempo y recursos a largo plazo.",[12,4453,4454,4455,4458,4459,1966,4462,4465],{},"De forma general el aprendizaje automático es un proceso que es ",[40,4456,4457],{},"parte de un sistema",", con un ",[40,4460,4461],{},"ciclo iterativo",[40,4463,4464],{},"orientado a generar valor"," que consta de varias etapas, cada una con sus propias tareas y desafíos.",[12,4467,4468,4472],{},[1882,4469],{"alt":4470,"src":4471},"Visión integradora del ciclo en Machine Learning","\u002Fblog\u002Fworkflow-machine-learning-projects\u002Fshared\u002Fmachine-learning-cycle.webp",[1887,4473,4474],{},"Ciclo en Machine Learning",[29,4476],{},[32,4478,4480],{"id":4479},"_1-definición-del-problema","1. Definición del problema",[12,4482,4483],{},"La primera etapa de cualquier proyecto de aprendizaje automático es la definición del problema:",[1359,4485,4486,4492,4498,4504],{},[1362,4487,4488,4491],{},[40,4489,4490],{},"Identificación del problema",": ¿Que queremos lograr con el proyecto? ¿Qué decisiones queremos apoyar con el modelo? Es crucial entender el contexto del negocio o la aplicación para definir claramente el problema.",[1362,4493,4494,4497],{},[40,4495,4496],{},"Variable objetivo",": ¿Cuál es la variable que queremos predecir o clasificar? Esta variable, también conocida como variable dependiente, es el foco del proyecto y debe ser claramente definida.",[1362,4499,4500,4503],{},[40,4501,4502],{},"Tipo de problema",": ¿Es un problema de clasificación, regresión, clustering, o algo más? La naturaleza del problema influirá en la elección de los algoritmos y técnicas a utilizar.",[1362,4505,4506,4509],{},[40,4507,4508],{},"Métricas de evaluación",": ¿Cómo vamos a medir el éxito del modelo? Es importante definir las métricas de evaluación desde el principio, ya que estas guiarán el desarrollo del modelo y la toma de decisiones a lo largo del proyecto.",[12,4511,4512],{},"Esta etapa es el cimiento de todo el proyecto. Un problema mal definido puede llevar a esfuerzos desperdiciados y resultados insatisfactorios. Es fundamental dedicar tiempo a entender el problema y establecer objetivos claros antes de avanzar a las siguientes etapas.",[12,4514,4515],{},"Veámos un ejemplo práctico:\nSupongamos que una empresa de comercio electrónico quiere predecir si un cliente realizará una compra en su sitio web. En este caso:",[1359,4517,4518,4523,4528,4533],{},[1362,4519,4520,4522],{},[40,4521,4490],{},": Predecir la probabilidad de que un cliente realice una compra.",[1362,4524,4525,4527],{},[40,4526,4496],{},": La variable objetivo podría ser una variable binaria que indique si el cliente realizó una compra (1) o no (0).",[1362,4529,4530,4532],{},[40,4531,4502],{},": Este es un problema de clasificación binaria.",[1362,4534,4535,4537],{},[40,4536,4508],{},": Las métricas de evaluación podrían incluir la precisión, el recall y el F1-score, dependiendo de la importancia relativa de los falsos positivos y los falsos negativos en el contexto del negocio.",[29,4539],{},[32,4541,4543],{"id":4542},"_2-recopilación-de-datos","2. Recopilación de datos",[12,4545,4546],{},"Una vez que el problema está claramente definido, el siguiente paso es la recopilación de datos, aquí se deben identificar y acceder a las fuentes de datos relevantes. Esto puede incluir:",[1359,4548,4549,4555,4561,4567],{},[1362,4550,4551,4554],{},[40,4552,4553],{},"Bases de datos internas\u002Fempresariales",": Datos almacenados en sistemas internos de la empresa, como bases de datos relacionales, data warehouses o data lakes. Algunos ejemplos incluyen registros de ventas, datos de clientes, datos provenientes de CRM o ERP, entre otros.",[1362,4556,4557,4560],{},[40,4558,4559],{},"APIs y servicios web",": Datos externos de proveedores de datos, redes sociales, servicios de geolocalización, etc. Por ejemplo, una empresa de análisis de sentimientos podría utilizar la API de Twitter para recopilar tweets relacionados con un tema específico.",[1362,4562,4563,4566],{},[40,4564,4565],{},"Logs y registros de eventos de sistemas",": Datos generados por aplicaciones, servidores, dispositivos IoT, etc. Por ejemplo, una empresa de monitoreo de infraestructura podría recopilar logs de servidores para detectar patrones de fallos.",[1362,4568,4569,4572],{},[40,4570,4571],{},"Datos públicos\u002Fexternos",": Datos disponibles públicamente, como conjuntos de datos de Kaggle, datos gubernamentales, datos de investigación académica, etc. Por ejemplo, un investigador podría utilizar el conjunto de datos de imágenes de MNIST para entrenar un modelo de reconocimiento de dígitos manuscritos.",[12,4574,4575],{},"Es importante tener en cuenta que la calidad de los datos recopilados es crucial para el éxito del proyecto. Los datos deben ser relevantes, completos, precisos y actualizados. Además, es fundamental considerar aspectos éticos y legales relacionados con la recopilación y el uso de datos, como la privacidad de los usuarios y el cumplimiento de regulaciones como GDPR.",[32,4577,4579],{"id":4578},"_3-preprocesamiento-de-datos","3. Preprocesamiento de datos",[12,4581,4582],{},"Esta es la fase de preparación y limpieza de datos,  es un paso crucial y a menudo es el mayor cuello de botella. Los prefesionales de datos suelen dedicar entre el 70% y el 80% de su tiempo a preparar datos y no a construir modelos.",[12,4584,4585],{},"La calidad del modelos depende directamente de la calidad de los datos, si están desordenados o incompletos, el modelo no podrá aprender patrones útiles. Incluso el algoritmo más sofisticado no puede compensar por datos de mala calidad.",[32,4587,4589],{"id":4588},"_4-análisis-exploratorio-de-datos-eda","4. Análisis exploratorio de datos (EDA)",[12,4591,4592],{},"Durante esta etapa, se realiza un análisis detallado de los datos para comprender su estructura, distribución y relaciones entre variables. Esto incluye:",[1359,4594,4595,4615,4632],{},[1362,4596,4597,4600,4601],{},[40,4598,4599],{},"Analisis univariado",": Examinar la distribución de cada variable individualmente, utilizando estadísticas descriptivas y visualizaciones como:\n",[1359,4602,4603,4606,4609,4612],{},[1362,4604,4605],{},"Histogramas",[1362,4607,4608],{},"Diagramas de caja (boxplots)",[1362,4610,4611],{},"Gráficos de barras",[1362,4613,4614],{},"Estadísticas de tendencia central (media, mediana) y dispersión (desviación estándar, rango intercuartílico)",[1362,4616,4617,4620,4621],{},[40,4618,4619],{},"Analisis bivariado",": Explorar las relaciones entre pares de variables, utilizando visualizaciones como:\n",[1359,4622,4623,4626,4629],{},[1362,4624,4625],{},"Diagramas de dispersión (scatter plots)",[1362,4627,4628],{},"Mapas de calor (heatmaps) para visualizar correlaciones",[1362,4630,4631],{},"Gráficos de barras apiladas para variables categóricas",[1362,4633,4634,4637,4638],{},[40,4635,4636],{},"Analisis multivariado",": Examinar las relaciones entre múltiples variables simultáneamente, utilizando técnicas como:\n",[1359,4639,4640,4643,4646],{},[1362,4641,4642],{},"Análisis de componentes principales (PCA)",[1362,4644,4645],{},"Análisis de clústeres",[1362,4647,4648],{},"Gráficos de pares (pair plots)\nEl EDA es fundamental para detectar problemas en los datos, como valores atípicos, distribuciones sesgadas o relaciones no lineales entre variables. Además, el EDA puede proporcionar insights valiosos que guiarán la selección de características y la elección de algoritmos en las etapas posteriores del proyecto.",[12,4650,4651],{},"Las herramientas comunes para realizar EDA incluye:",[1359,4653,4654,4660,4665,4671],{},[1362,4655,4656,4659],{},[40,4657,4658],{},"Python",": Bibliotecas como Pandas, Matplotlib, Seaborn y Plotly son ampliamente utilizadas para el análisis exploratorio de datos en Python.",[1362,4661,4662,4664],{},[40,4663,3706],{},": Paquetes como ggplot2, dplyr y tidyr son populares para realizar EDA en R.",[1362,4666,4667,4670],{},[40,4668,4669],{},"Herramientas de visualización",": Herramientas como Tableau, Power BI o QlikView también pueden ser utilizadas para realizar análisis exploratorio de datos de manera interactiva.",[1362,4672,4673,4676],{},[40,4674,4675],{},"Jupyter Notebooks",": Los notebooks de Jupyter son una herramienta común para realizar EDA, ya que permiten combinar código, visualizaciones y texto explicativo en un solo documento.",[2073,4678,4679],{},[12,4680,4681],{},"El EDA no es un paso lineal, a menudo se realiza de manera iterativa a medida que se descubren nuevos insights o se identifican problemas en los datos. Es importante documentar los hallazgos del EDA, ya que estos pueden ser útiles para la toma de decisiones en las etapas posteriores del proyecto.",[53,4683,4685],{"id":4684},"principios-para-un-eda-efectivo","Principios para un EDA efectivo",[1359,4687,4688,4694,4700,4709],{},[1362,4689,4690,4693],{},[40,4691,4692],{},"Comenzar simple",": Iniciar con visualizaciones y estadísticas básicas para obtener una comprensión general de los datos antes de profundizar en análisis más complejos.",[1362,4695,4696,4699],{},[40,4697,4698],{},"Colores con propósito",": Utilizar colores de manera estratégica para resaltar patrones o diferencias importantes en los datos, evitando el uso excesivo de colores que pueda distraer.",[1362,4701,4702,4705,4708],{},[40,4703,4704],{},"Proceso iterativo",[4706,4707],"iterar",{}," continuamente a medida que se descubren nuevos insights o se identifican problemas en los datos, ajustando el enfoque del EDA según sea necesario.",[1362,4710,4711,4714],{},[40,4712,4713],{},"Documentar hallazgos",": Registrar los insights y descubrimientos del EDA para facilitar la toma de decisiones en las etapas posteriores del proyecto y para compartir con otros miembros del equipo.",[32,4716,4718],{"id":4717},"_5-feature-engineering","5. Feature engineering",[12,4720,4721],{},"El feature engineering es el proceso de crear nuevas características a partir de los datos originales para mejorar el rendimiento del modelo. Es el puente entre datos crudos sin estructurar y entradas listas para modelar. Esta etapa es crucial porque nos ayuda a:",[1359,4723,4724,4730,4736,4742],{},[1362,4725,4726,4729],{},[40,4727,4728],{},"Mejorar precisión",": Las características bien diseñadas pueden capturar patrones complejos en los datos que los modelos pueden aprovechar para hacer mejores predicciones.",[1362,4731,4732,4735],{},[40,4733,4734],{},"Reducir sobreajuste",": Al crear características más relevantes, podemos ayudar a los modelos a generalizar mejor a datos no vistos, reduciendo el riesgo de sobreajuste.",[1362,4737,4738,4741],{},[40,4739,4740],{},"Facilitar la interpretación",": Las características bien diseñadas pueden hacer que los modelos sean más interpretables, lo que es especialmente importante en aplicaciones donde la explicabilidad es crucial.",[1362,4743,4744,4747],{},[40,4745,4746],{},"Aumentar la eficiencia",": Al reducir la dimensionalidad de los datos o crear características más informativas, podemos mejorar la eficiencia del entrenamiento del modelo.",[12,4749,4750],{},"Algunas técnicas fundamentales de feature engineering incluyen:",[53,4752,4754],{"id":4753},"transformaciones-numéricas","Transformaciones Numéricas",[1359,4756,4757,4777],{},[1362,4758,4759,4762,4763],{},[40,4760,4761],{},"Escalado",": Útil para modelos sensibles a magnitudes (Regresión, SVM, KNN, redes neuronales).",[1359,4764,4765,4771,4774],{},[1362,4766,4767,4768],{},"Min-Max Scaling: Lleva valores a rango ",[83,4769,4770],{},"0,1",[1362,4772,4773],{},"Standardization (Z-score): media 0, desviación 1",[1362,4775,4776],{},"Robust Scaling: usa mediana y rango intercuartílico (mejor con outliers)",[1362,4778,4779,4782,4783],{},[40,4780,4781],{},"Transformaciones no lineales",": Cuando la relación no es lineal.",[1359,4784,4785,4791,4797,4808],{},[1362,4786,4787,4788],{},"Log transform: ",[61,4789,4790],{},"log(x)",[1362,4792,4793,4794],{},"Raíz cuadrada: ",[61,4795,4796],{},"sqrt(x)",[1362,4798,4799,4800,4803,4804,4807],{},"Box-Cox: ",[61,4801,4802],{},"((x + 1)^λ - 1) \u002F λ"," (para λ ≠ 0) o ",[61,4805,4806],{},"log(x + 1)"," (para λ = 0)",[1362,4809,4810],{},"Yeo-Johnson: Similar a Box-Cox pero para datos con valores negativos\nMuy útil cuando hay distribuciones muy sesgadas.",[53,4812,4814],{"id":4813},"variables-categóricas","Variables Categóricas",[1359,4816,4817],{},[1362,4818,4819,4822],{},[40,4820,4821],{},"One-Hot Encoding",": Convierte categorías en columnas binarias.",[12,4824,4825],{},"Ejemplo:",[74,4827,4830],{"className":4828,"code":4829,"language":2235},[2816],"Color: [Rojo, Azul, Verde]\n\nPasan a ser:\n\nRojo  Azul  Verde\n1     0     0\n",[61,4831,4829],{"__ignoreMap":79},[1359,4833,4834],{},[1362,4835,4836,4839],{},[40,4837,4838],{},"Ordinal Encoding",": Cuando hay orden:",[74,4841,4844],{"className":4842,"code":4843,"language":2235},[2816],"Bajo \u003C Medio \u003C Alto\n",[61,4845,4843],{"__ignoreMap":79},[1359,4847,4848],{},[1362,4849,4850,4853],{},[40,4851,4852],{},"Target Encoding",": Reemplaza categoría por promedio del target:",[74,4855,4858],{"className":4856,"code":4857,"language":2235},[2816],"Ciudad → promedio de ventas\n",[61,4859,4857],{"__ignoreMap":79},[1359,4861,4862],{},[1362,4863,4864,4867],{},[40,4865,4866],{},"Frequency Encoding",": Reemplaza categoría por frecuencia de aparición.",[53,4869,4871],{"id":4870},"features-temporales","Features Temporales",[12,4873,4874],{},"Si se trabaja con fechas:",[1359,4876,4877,4880,4883,4886,4889,4892,4895,4898],{},[1362,4878,4879],{},"Año",[1362,4881,4882],{},"Mes",[1362,4884,4885],{},"Día",[1362,4887,4888],{},"Día de la semana",[1362,4890,4891],{},"Es fin de semana",[1362,4893,4894],{},"Trimestre",[1362,4896,4897],{},"Diferencia entre fechas",[1362,4899,4900],{},"Tiempo desde último evento",[1359,4902,4903],{},[1362,4904,4905,4908],{},[40,4906,4907],{},"Codificación cíclica",": Para variables como hora o mes:",[74,4910,4913],{"className":4911,"code":4912,"language":2235},[2816],"sin(2π * hora \u002F 24)\ncos(2π * hora \u002F 24)\n",[61,4914,4912],{"__ignoreMap":79},[12,4916,4917],{},"Evita que 23 y 0 parezcan \"lejanos\".",[53,4919,4921],{"id":4920},"interacciones-entre-variables","Interacciones entre Variables",[12,4923,4924],{},"A veces la combinación importa más que la variable sola.",[1359,4926,4927,4936,4948,4956],{},[1362,4928,4929,4932,4933],{},[40,4930,4931],{},"Producto de variables",": ",[61,4934,4935],{},"x1 * x2",[1362,4937,4938,4932,4941,4944,4945],{},[40,4939,4940],{},"Polinomios",[61,4942,4943],{},"x^2",", ",[61,4946,4947],{},"x^3",[1362,4949,4950,4932,4953],{},[40,4951,4952],{},"Ratios",[61,4954,4955],{},"precio \u002F tamaño",[1362,4957,4958,4932,4961],{},[40,4959,4960],{},"Diferencias",[61,4962,4963],{},"fecha_pago - fecha_registro",[12,4965,4966],{},"Muy usado en modelos lineales.",[53,4968,4970],{"id":4969},"binning-discretización","Binning (Discretización)",[12,4972,4973],{},"Convertir numéricos en categorías:",[1359,4975,4976,4981,4986],{},[1362,4977,4978],{},[40,4979,4980],{},"Binning uniforme",[1362,4982,4983],{},[40,4984,4985],{},"Binning por cuantiles",[1362,4987,4988],{},[40,4989,4990],{},"Binning basado en negocio",[12,4992,4825],{},[74,4994,4997],{"className":4995,"code":4996,"language":2235},[2816],"Edad → [0-18], [19-35], [36-60], 60+\n",[61,4998,4996],{"__ignoreMap":79},[53,5000,5002],{"id":5001},"manejo-de-outliers","Manejo de Outliers",[1359,5004,5005,5010,5015,5020],{},[1362,5006,5007],{},[40,5008,5009],{},"Clipping",[1362,5011,5012],{},[40,5013,5014],{},"Winsorizing",[1362,5016,5017],{},[40,5018,5019],{},"Log transform",[1362,5021,5022,4932,5025],{},[40,5023,5024],{},"Crear feature binaria",[61,5026,5027],{},"es_outlier",[53,5029,5031],{"id":5030},"features-basadas-en-agrupaciones","Features basadas en agrupaciones",[12,5033,5034],{},"Muy potente en datasets transaccionales.",[12,5036,4825],{},[1359,5038,5039,5042,5045,5048],{},[1362,5040,5041],{},"Promedio de compras por usuario",[1362,5043,5044],{},"Número de pedidos",[1362,5046,5047],{},"Tiempo desde última compra",[1362,5049,5050],{},"Máximo \u002F mínimo histórico",[53,5052,5054],{"id":5053},"feature-selection","Feature Selection",[12,5056,5057],{},"No todo es crear - también eliminar.",[1359,5059,5060,5062,5065,5068,5071],{},[1362,5061,3084],{},[1362,5063,5064],{},"Mutual information",[1362,5066,5067],{},"RFE",[1362,5069,5070],{},"Lasso (L1)",[1362,5072,5073],{},"Feature importance (árboles)",[12,5075,5076],{},"El feature engineering es una de las habilidades más valiosas en la ciencia de datos, ya que puede marcar la diferencia entre un modelo mediocre y uno excepcional.",[32,5078,5080],{"id":5079},"_6-entrenamiento-de-modelos","6. Entrenamiento de modelos",[12,5082,5083],{},"Una vez que los datos están preparados y las características han sido diseñadas, el siguiente paso es entrenar un modelo de aprendizaje automático.",[12,5085,5086],{},"En esta etapa, se selecciona un algoritmo de aprendizaje automático adecuado para el problema definido y se ajusta a los datos de entrenamiento. El proceso de entrenamiento implica alimentar el modelo con los datos y permitir que aprenda patrones y relaciones para hacer predicciones.",[12,5088,5089],{},"Lo primero que debemos tener en cuenta antes de empezar es la división de los datos (datasets) en conjuntos de entrenamiento, validación y prueba. Esto es crucial para evaluar el rendimiento del modelo de manera justa y evitar el sobreajuste:",[1359,5091,5092,5098,5104],{},[1362,5093,5094,5097],{},[40,5095,5096],{},"Conjunto de entrenamiento (Training Set) - (70-80%)",": Es el conjunto de datos que se utiliza para entrenar el modelo. El modelo aprende a partir de estos datos, ajustando sus parámetros para minimizar el error en las predicciones.",[1362,5099,5100,5103],{},[40,5101,5102],{},"Conjunto de validación (Validation Set) - (10-15%)",": Es un conjunto de datos separado que se utiliza para ajustar los hiperparámetros del modelo y tomar decisiones sobre la arquitectura del modelo. El modelo no se entrena directamente con estos datos, pero se utilizan para evaluar su rendimiento durante el proceso de entrenamiento.",[1362,5105,5106,5109],{},[40,5107,5108],{},"Conjunto de prueba (Test Set) - (10-15%)",": Es un conjunto de datos completamente separado que se utiliza para evaluar el rendimiento final del modelo después de que se ha completado el entrenamiento y la selección de hiperparámetros. Este conjunto no se utiliza en absoluto durante el proceso de entrenamiento o validación, lo que permite obtener una evaluación imparcial del modelo.",[2073,5111,5112],{},[12,5113,5114],{},"Como dato, si utilizas agentes de IA para el desarrollo de software, una buena práctica es utilizar distintas sesiones o agentes para cada etapa del desarrollo, un agente para la generación de código, otro para la revisión y otro para las pruebas. En este otro caso ayuda a que la IA no sea autoreferencial y pueda detectar errores que un mismo agente podría pasar por alto.",[12,5116,5117],{},"Para el entrenamiento del modelo, se selecciona un algoritmo de aprendizaje automático adecuado para el tipo de problema que se está abordando (clasificación, regresión, clustering, etc.). Algunos ejemplos de algoritmos comunes, como ya los vimos son:",[1359,5119,5120,5126,5132,5138,5144,5150],{},[1362,5121,5122,5125],{},[40,5123,5124],{},"Regresión lineal",": Modelo simple para relaciones lineales, rápido, interpretable, pero limitado a relaciones lineales.",[1362,5127,5128,5131],{},[40,5129,5130],{},"Árboles de decisión",": Modelos basados en reglas, fáciles de interpretar, pero propensos a sobreajuste.",[1362,5133,5134,5137],{},[40,5135,5136],{},"Random Forest",": Conjunto de árboles de decisión, reduce sobreajuste, pero menos interpretable.",[1362,5139,5140,5143],{},[40,5141,5142],{},"Gradient Boosting (XGBoost, LightGBM)",": Potente para datos tabulares, pero puede ser lento y propenso a sobreajuste si no se ajusta correctamente.",[1362,5145,5146,5149],{},[40,5147,5148],{},"Redes neuronales",": Modelos inspirados en el cerebro, capaces de capturar relaciones complejas, pero requieren grandes cantidades de datos y son menos interpretables.",[1362,5151,5152,5155],{},[40,5153,5154],{},"Support Vector Machines (SVM)",": Efectivo para problemas de clasificación, pero puede ser lento con grandes conjuntos de datos.",[32,5157,5159],{"id":5158},"_7-evaluación-del-modelo","7. Evaluación del modelo",[12,5161,5162],{},"Una vez que el modelo ha sido entrenado, es crucial evaluar su rendimiento utilizando el conjunto de validación y el conjunto de prueba. La evaluación del modelo implica medir su capacidad para hacer predicciones precisas y generalizar a datos no vistos.\nLas métricas de evaluación varían según el tipo de problema que se esté abordando. Para problemas de clasificación, algunas métricas comunes incluyen:",[1359,5164,5165,5171,5177,5183,5189,5195,5201],{},[1362,5166,5167,5170],{},[40,5168,5169],{},"Precisión",": Proporción de predicciones correctas sobre el total de predicciones realizadas.",[1362,5172,5173,5176],{},[40,5174,5175],{},"Recall (Sensibilidad)",": Proporción de verdaderos positivos sobre el total de positivos reales.",[1362,5178,5179,5182],{},[40,5180,5181],{},"F1-score",": La media armónica de la precisión y el recall, útil cuando hay un desequilibrio entre clases.",[1362,5184,5185,5188],{},[40,5186,5187],{},"AUC-ROC",": Área bajo la curva ROC, que mide la capacidad del modelo para distinguir entre clases.\nPara problemas de regresión, algunas métricas comunes incluyen:",[1362,5190,5191,5194],{},[40,5192,5193],{},"Error cuadrático medio (MSE)",": Promedio de los cuadrados de los errores entre las predicciones y los valores reales.",[1362,5196,5197,5200],{},[40,5198,5199],{},"Error absoluto medio (MAE)",": Promedio de los valores absolutos de los errores entre las predicciones y los valores reales.",[1362,5202,5203,5206],{},[40,5204,5205],{},"R² (Coeficiente de determinación)",": Proporción de la varianza en la variable dependiente que es predecible a partir de las variables independientes.",[53,5208,5210],{"id":5209},"matriz-de-confusión","Matriz de confusión",[12,5212,5213],{},"Una herramienta útil para evaluar modelos de clasificación es la matriz de confusión, que muestra el número de verdaderos positivos, falsos positivos, verdaderos negativos y falsos negativos. Esto permite entender mejor el rendimiento del modelo y las áreas donde puede estar cometiendo errores.",[3070,5215,5216,5228],{},[3073,5217,5218],{},[3076,5219,5220,5222,5225],{},[3079,5221],{},[3079,5223,5224],{},"Predicción Positiva",[3079,5226,5227],{},"Predicción Negativa",[3086,5229,5230,5243],{},[3076,5231,5232,5237,5240],{},[3091,5233,5234],{},[40,5235,5236],{},"Real Positivo",[3091,5238,5239],{},"Verdaderos Positivos (TP)",[3091,5241,5242],{},"Falsos Negativos (FN)",[3076,5244,5245,5250,5253],{},[3091,5246,5247],{},[40,5248,5249],{},"Real Negativo",[3091,5251,5252],{},"Falsos Positivos (FP)",[3091,5254,5255],{},"Verdaderos Negativos (TN)",[53,5257,5259],{"id":5258},"curva-roc","Curva ROC",[12,5261,5262],{},"La curva ROC (Receiver Operating Characteristic) es una herramienta gráfica que muestra la relación entre la tasa de verdaderos positivos (TPR) y la tasa de falsos positivos (FPR) a medida que se varía el umbral de clasificación. El área bajo la curva ROC (AUC-ROC) es una métrica que mide la capacidad del modelo para distinguir entre clases, con un valor de 1 indicando un modelo perfecto y un valor de 0.5 indicando un modelo sin capacidad de discriminación.",[53,5264,5266],{"id":5265},"curva-precision-recall","Curva Precision-Recall",[12,5268,5269],{},"La curva Precision-Recall es otra herramienta gráfica que muestra la relación entre la precisión y el recall a medida que se varía el umbral de clasificación. Esta curva es especialmente útil cuando hay un desequilibrio entre clases, ya que se enfoca en la capacidad del modelo para identificar correctamente la clase minoritaria.",[32,5271,5273],{"id":5272},"_8-implementación-y-despliegue","8. Implementación y despliegue",[12,5275,5276],{},"Una vez que el modelo ha sido entrenado y evaluado, el siguiente paso es implementarlo en un entorno de producción para que pueda ser utilizado por los usuarios finales o integrado en sistemas existentes. La implementación y el despliegue de modelos de aprendizaje automático pueden ser desafiantes debido a la necesidad de garantizar la escalabilidad, la seguridad y la mantenibilidad del modelo en un entorno de producción. Algunas consideraciones clave para la implementación y el despliegue de modelos de aprendizaje automático incluyen:",[1359,5278,5279,5285,5291,5297,5303],{},[1362,5280,5281,5284],{},[40,5282,5283],{},"APIs",": Exponer el modelo a través de una API RESTful o gRPC para que pueda ser consumido por otras aplicaciones o servicios.",[1362,5286,5287,5290],{},[40,5288,5289],{},"Aplicaciones web",": Integrar el modelo en una aplicación web para que los usuarios puedan interactuar con él a través de una interfaz gráfica.",[1362,5292,5293,5296],{},[40,5294,5295],{},"Integraciones con sistemas existentes",": Integrar el modelo en sistemas empresariales existentes, como CRM, ERP o sistemas de recomendación.",[1362,5298,5299,5302],{},[40,5300,5301],{},"Contenedores y orquestación",": Utilizar contenedores (Docker) y herramientas de orquestación (Kubernetes) para facilitar el despliegue, la escalabilidad y la gestión del modelo en producción.",[1362,5304,5305,5308],{},[40,5306,5307],{},"Monitoreo y mantenimiento",": Implementar sistemas de monitoreo para rastrear el rendimiento del modelo en producción, detectar posibles problemas y realizar actualizaciones o retrainings según sea necesario.",[32,5310,5312],{"id":5311},"_9-monitoreo-y-mantenimiento","9. Monitoreo y mantenimiento",[12,5314,5315],{},"Una vez que el modelo está en producción, es crucial monitorear su rendimiento de manera continua para asegurarse de que sigue siendo efectivo y relevante. El monitoreo del modelo implica rastrear métricas clave, detectar posibles problemas y realizar ajustes o retrainings según sea necesario. Algunos problemas que pueden surgir en esta etapa incluyen:",[1359,5317,5318,5324,5330],{},[1362,5319,5320,5323],{},[40,5321,5322],{},"Deriva de datos (Data Drift)",": Ocurre cuando la distribución de los datos de entrada cambia con el tiempo, lo que puede afectar negativamente el rendimiento del modelo. Es importante monitorear la distribución de los datos y realizar retrainings si se detecta una deriva significativa.",[1362,5325,5326,5329],{},[40,5327,5328],{},"Deriva de concepto (Concept Drift)",": Ocurre cuando la relación entre las características y la variable objetivo cambia con el tiempo, lo que puede hacer que el modelo sea menos efectivo. Es importante monitorear el rendimiento del modelo y realizar ajustes o retrainings si se detecta una deriva de concepto.",[1362,5331,5332,5335],{},[40,5333,5334],{},"Training-serving skew",": Ocurre cuando hay diferencias entre los datos utilizados para entrenar el modelo y los datos que se encuentran en producción, lo que puede afectar negativamente el rendimiento del modelo. Es importante asegurarse de que los datos de entrenamiento sean representativos de los datos en producción y realizar ajustes si se detecta un skew significativo.",[12,5337,5338],{},"Para lograr un buen monitoreo se pueden tomar algunas buenas prácticas, como:",[1359,5340,5341,5347,5353,5359,5365,5371],{},[1362,5342,5343,5346],{},[40,5344,5345],{},"Definir KPIs claros",": Establecer métricas clave de rendimiento (KPIs) para monitorear el modelo, como precisión, recall, F1-score, AUC-ROC, etc.",[1362,5348,5349,5352],{},[40,5350,5351],{},"Implementar alertas",": Configurar alertas para notificar al equipo cuando el rendimiento del modelo cae por debajo de un umbral predefinido o cuando se detecta una deriva significativa.",[1362,5354,5355,5358],{},[40,5356,5357],{},"Diversificar metricas",": Monitorear múltiples métricas para obtener una visión completa del rendimiento del modelo y detectar posibles problemas desde diferentes ángulos.",[1362,5360,5361,5364],{},[40,5362,5363],{},"Automatizar retrainings",": Configurar procesos automatizados para realizar retrainings del modelo cuando se detecta una deriva significativa o cuando el rendimiento cae por debajo de un umbral predefinido.",[1362,5366,5367,5370],{},[40,5368,5369],{},"Documentar cambios",": Mantener un registro de los cambios realizados en el modelo, como ajustes de hiperparámetros, cambios en los datos de entrenamiento, etc., para facilitar la trazabilidad y la comprensión de las decisiones tomadas.",[1362,5372,5373,5376],{},[40,5374,5375],{},"Versionar modelos",": Utilizar herramientas de versionado de modelos para mantener un historial de las diferentes versiones del modelo y facilitar la gestión de cambios y actualizaciones.",[12,5378,5379],{},"Normalmente el proceso de mantenimiento lleva un proceso como el siguiente:",[1406,5381,5382,5388,5394,5400,5406],{},[1362,5383,5384,5387],{},[40,5385,5386],{},"Monitoreo continuo",": Rastrear el rendimiento del modelo en producción utilizando las métricas clave definidas.",[1362,5389,5390,5393],{},[40,5391,5392],{},"Detección de problemas",": Identificar posibles problemas, como deriva de datos, deriva de concepto o training-serving skew, a través del monitoreo de métricas y alertas.",[1362,5395,5396,5399],{},[40,5397,5398],{},"Análisis de causas",": Investigar las causas subyacentes de los problemas detectados, como cambios en la distribución de los datos, cambios en el comportamiento de los usuarios, etc.",[1362,5401,5402,5405],{},[40,5403,5404],{},"Ajustes o retrainings",": Realizar ajustes en el modelo o realizar retrainings utilizando nuevos datos para abordar los problemas detectados y mejorar el rendimiento del modelo.",[1362,5407,5408,5411],{},[40,5409,5410],{},"Validar y desplegar",": Validar el rendimiento del modelo ajustado o retrained utilizando el conjunto de validación y luego desplegar la nueva versión del modelo en producción.",[12,5413,5414],{},"Algunas herramientas populares para el monitoreo y mantenimiento de modelos de aprendizaje automático incluyen:",[1359,5416,5417,5423,5429,5435],{},[1362,5418,5419,5422],{},[40,5420,5421],{},"Prometheus",": Sistema de monitoreo y alerta de código abierto que se puede utilizar para rastrear métricas de rendimiento del modelo en producción.",[1362,5424,5425,5428],{},[40,5426,5427],{},"Grafana",": Plataforma de visualización de datos que se puede integrar con Prometheus para crear paneles de control personalizados para monitorear el rendimiento del modelo.",[1362,5430,5431,5434],{},[40,5432,5433],{},"MLflow",": Plataforma de código abierto para la gestión del ciclo de vida de los modelos de aprendizaje automático, que incluye funcionalidades para el monitoreo y mantenimiento de modelos en producción.",[1362,5436,5437,5440],{},[40,5438,5439],{},"Evidently AI",": Evidently AI es una plataforma de código abierto y basada en la nube para evaluar, probar y supervisar sistemas de IA y aprendizaje automático.",[29,5442],{},[32,5444,5446],{"id":5445},"caso-práctico-predicción-de-abandono-churn-en-una-fintech","Caso práctico: Predicción de abandono (churn) en una fintech",[12,5448,5449],{},"Haremos un recorrido por un caso práctico simulado de un proyecto de aprendizaje automático para predecir el abandono (churn) en una fintech de suscripciones digitales. En este caso ilustraremos el conocimiento que tenemos hasta ahora sobre el flujo de un proyecto de aprendizaje automático.",[12,5451,5452],{},[40,5453,5454],{},"Contexto del negocio",[12,5456,5457],{},"Una fintech de suscripciones digitales tiene:",[1359,5459,5460,5465,5471,5477],{},[1362,5461,5462],{},[40,5463,5464],{},"120,000 usuarios activos",[1362,5466,5467,5468],{},"Suscripción mensual promedio: ",[40,5469,5470],{},"$25",[1362,5472,5473,5474],{},"Ingreso mensual recurrente (MRR): ",[40,5475,5476],{},"$3,000,000",[1362,5478,5479,5480],{},"Tasa de abandono mensual (churn): ",[40,5481,5482],{},"8%",[12,5484,5485],{},"Eso significa que cada mes:",[74,5487,5490],{"className":5488,"code":5489,"language":2235},[2816],"120,000 × 8% = 9,600 usuarios cancelan\n",[61,5491,5489],{"__ignoreMap":79},[12,5493,5494],{},"Pérdida mensual estimada:",[74,5496,5499],{"className":5497,"code":5498,"language":2235},[2816],"9,600 × $25 = $240,000\n",[61,5500,5498],{"__ignoreMap":79},[12,5502,5503,5504,5507],{},"La empresa quiere reducir el churn al ",[40,5505,5506],{},"6%",", lo que implicaría ahorrar:",[74,5509,5512],{"className":5510,"code":5511,"language":2235},[2816],"2% × 120,000 × $25 = $60,000 mensuales\n",[61,5513,5511],{"__ignoreMap":79},[12,5515,5516,5517,5520],{},"El objetivo del proyecto de Machine Learning es ",[40,5518,5519],{},"identificar usuarios con alta probabilidad de cancelar en los próximos 30 días",", para enviarles una campaña de retención personalizada.",[53,5522,5524],{"id":5523},"definición-del-problema","Definición del problema",[1359,5526,5527],{},[1362,5528,5529],{},[40,5530,4490],{},[12,5532,5533],{},"Reducir la tasa de abandono mensual del 8% al 6%.",[1359,5535,5536],{},[1362,5537,5538],{},[40,5539,4496],{},[12,5541,5542,624],{},[61,5543,5544],{},"churn_30d",[74,5546,5549],{"className":5547,"code":5548,"language":2235},[2816],"1 - Cancela en los próximos 30 días\n0 - No cancela\n",[61,5550,5548],{"__ignoreMap":79},[1359,5552,5553],{},[1362,5554,5555],{},[40,5556,4502],{},[12,5558,5559],{},"Clasificación binaria.",[1359,5561,5562],{},[1362,5563,5564],{},[40,5565,5566],{},"Métrica de negocio clave",[12,5568,5569],{},"No basta con accuracy (es decir , la tasa de acierto general). Lo importante es:",[74,5571,5574],{"className":5572,"code":5573,"language":2235},[2816],"Recall de la clase churn\nROI de la campaña de retención\n",[61,5575,5573],{"__ignoreMap":79},[12,5577,5578],{},"¿Por qué? Porque queremos identificar correctamente a los usuarios que van a cancelar (recall) y asegurarnos de que la campaña de retención sea rentable (ROI).",[53,5580,5582],{"id":5581},"recopilación-de-datos","Recopilación de datos",[12,5584,5585],{},"Se recopilaron datos de:",[1359,5587,5588],{},[1362,5589,5590],{},[40,5591,5592],{},"Fuentes internas",[74,5594,5597],{"className":5595,"code":5596,"language":2235},[2816],"* Historial de pagos\n* Frecuencia de uso de la app\n* Tiempo desde último login\n* Tickets de soporte\n* Tipo de plan\n* Método de pago\n* Historial de fallos de pago\n",[61,5598,5596],{"__ignoreMap":79},[1359,5600,5601],{},[1362,5602,5603],{},[40,5604,5605],{},"Volumen de datos",[74,5607,5610],{"className":5608,"code":5609,"language":2235},[2816],"* 18 meses de histórico\n* 1.5 millones de registros mensuales\n* Dataset final: **95,000 usuarios únicos** con historial completo\n",[61,5611,5609],{"__ignoreMap":79},[53,5613,5615],{"id":5614},"preprocesamiento","Preprocesamiento",[12,5617,5618],{},"Problemas detectados:",[74,5620,5623],{"className":5621,"code":5622,"language":2235},[2816],"* 7% valores nulos en \"último login\"\n* 3% registros duplicados\n* Variables categóricas con alta cardinalidad (ciudades)\n",[61,5624,5622],{"__ignoreMap":79},[12,5626,5627],{},"Acciones tomadas:",[74,5629,5632],{"className":5630,"code":5631,"language":2235},[2816],"* Imputación con mediana para variables numéricas\n* Eliminación de duplicados\n* Agrupación de ciudades poco frecuentes como \"Otras\"\n",[61,5633,5631],{"__ignoreMap":79},[12,5635,5636,5637],{},"Tiempo invertido en esta etapa: ",[40,5638,5639],{},"72% del proyecto",[53,5641,5643],{"id":5642},"análisis-exploratorio","Análisis Exploratorio",[12,5645,5646],{},"Hallazgos clave:",[1359,5648,5649],{},[1362,5650,5651],{},[40,5652,5653],{},"Insight 1",[12,5655,5656],{},"Usuarios que no inician sesión en 14 días tienen:",[74,5658,5661],{"className":5659,"code":5660,"language":2235},[2816],"* 22% probabilidad de churn\n  vs\n* 4% en usuarios activos recientes\n",[61,5662,5660],{"__ignoreMap":79},[1359,5664,5665],{},[1362,5666,5667],{},[40,5668,5669],{},"Insight 2",[12,5671,5672],{},"Usuarios con más de 2 fallos de pago en 60 días:",[74,5674,5677],{"className":5675,"code":5676,"language":2235},[2816],"* 35% probabilidad de churn\n",[61,5678,5676],{"__ignoreMap":79},[1359,5680,5681],{},[1362,5682,5683],{},[40,5684,5685],{},"Insight 3",[12,5687,5688],{},"Usuarios que abrieron más de 3 tickets de soporte:",[74,5690,5693],{"className":5691,"code":5692,"language":2235},[2816],"* 18% churn\n* Principal causa: problemas técnicos\n",[61,5694,5692],{"__ignoreMap":79},[12,5696,5697],{},"Esto nos cambia el enfoque: no solo es un problema de retención, sino también de experiencia del usuario y soporte técnico. Estos datos nos están diciendo que los usuarios que tienen problemas técnicos o dificultades para usar la app son mucho más propensos a cancelar, lo que sugiere que una campaña de retención efectiva también debería abordar estos problemas y mejorar la experiencia del usuario.",[53,5699,4333],{"id":5700},"feature-engineering",[12,5702,5703],{},"Se crearon variables como:",[1359,5705,5706,5712,5718,5724,5730,5736,5742],{},[1362,5707,5708,5711],{},[61,5709,5710],{},"dias_desde_ultimo_login",": Es la cantidad de días desde la última vez que el usuario inició sesión en la aplicación. Esta variable es importante porque, como se descubrió en el análisis exploratorio, los usuarios que no inician sesión en un período prolongado tienen una mayor probabilidad de cancelar su suscripción.",[1362,5713,5714,5717],{},[61,5715,5716],{},"numero_fallos_pago_60d",": Es el número de fallos de pago que un usuario ha tenido en los últimos 60 días. Como se descubrió en el EDA, los usuarios con más de 2 fallos de pago en este período tienen una probabilidad significativamente mayor de cancelar su suscripción.",[1362,5719,5720,5723],{},[61,5721,5722],{},"promedio_uso_semanal",": Es el promedio de uso de la aplicación por semana. Esta variable puede ayudar a capturar el nivel de compromiso del usuario con la aplicación, lo que puede ser un indicador importante de su probabilidad de cancelar.",[1362,5725,5726,5729],{},[61,5727,5728],{},"tiempo_cliente_meses",": Usuarios que han sido clientes por más tiempo pueden tener una menor probabilidad de cancelar.",[1362,5731,5732,5735],{},[61,5733,5734],{},"tickets_soporte_90d",": Es el número de tickets de soporte que un usuario ha abierto en los últimos 90 días. Dado que se descubrió que los usuarios que abren más de 3 tickets de soporte tienen una mayor probabilidad de cancelar, esta variable puede ser un indicador importante del riesgo de churn.",[1362,5737,5738,5741],{},[61,5739,5740],{},"ratio_fallos_pago = fallos \u002F intentos",": Este ratio puede ser un indicador más preciso del riesgo de churn relacionado con los problemas de pago, ya que tiene en cuenta tanto el número de fallos como el número total de intentos de pago.",[1362,5743,5744,5745,5748],{},"Variable binaria: ",[61,5746,5747],{},"es_usuario_nuevo (\u003C3 meses)",": Los usuarios nuevos pueden tener un riesgo diferente de churn en comparación con los usuarios más antiguos, por lo que esta variable puede ayudar a capturar esa diferencia.",[12,5750,5751],{},"También se creó:",[74,5753,5756],{"className":5754,"code":5755,"language":2235},[2816],"riesgo_inactividad = dias_desde_ultimo_login × (1 \u002F promedio_uso)\n",[61,5757,5755],{"__ignoreMap":79},[12,5759,5760,5761,5764],{},"Esta variable compuesta puede ser un indicador poderoso del riesgo de churn, ya que combina la información sobre la inactividad del usuario (días desde el último login) con su nivel de compromiso (promedio de uso semanal). Un valor alto de ",[61,5762,5763],{},"riesgo_inactividad"," indicaría que un usuario no ha iniciado sesión en mucho tiempo y tiene un bajo nivel de uso, lo que podría ser un fuerte indicador de que está en riesgo de cancelar su suscripción.",[53,5766,5768],{"id":5767},"entrenamiento-de-modelos","Entrenamiento de modelos",[12,5770,5771],{},"Se dividieron datos:",[1359,5773,5774,5777,5780],{},[1362,5775,5776],{},"75% entrenamiento",[1362,5778,5779],{},"15% validación",[1362,5781,5782],{},"10% prueba",[12,5784,5785],{},"Se probaron:",[3070,5787,5788,5800],{},[3073,5789,5790],{},[3076,5791,5792,5795,5797],{},[3079,5793,5794],{},"Modelo",[3079,5796,5187],{},[3079,5798,5799],{},"Recall churn",[3086,5801,5802,5813,5823,5834],{},[3076,5803,5804,5807,5810],{},[3091,5805,5806],{},"Regresión Logística",[3091,5808,5809],{},"0.76",[3091,5811,5812],{},"0.58",[3076,5814,5815,5817,5820],{},[3091,5816,5136],{},[3091,5818,5819],{},"0.84",[3091,5821,5822],{},"0.71",[3076,5824,5825,5828,5831],{},[3091,5826,5827],{},"XGBoost",[3091,5829,5830],{},"0.87",[3091,5832,5833],{},"0.78",[3076,5835,5836,5839,5842],{},[3091,5837,5838],{},"Red neuronal",[3091,5840,5841],{},"0.85",[3091,5843,5844],{},"0.73",[12,5846,5847,5848,5850],{},"Aunque XGBoost tenía mejor métrica, se eligió ",[40,5849,5136],{}," inicialmente porque:",[1359,5852,5853,5856,5859],{},[1362,5854,5855],{},"Era más interpretable",[1362,5857,5858],{},"Menor riesgo de sobreajuste",[1362,5860,5861],{},"Más fácil de mantener",[12,5863,5864,5865,133],{},"Esto es clave: ",[40,5866,5867],{},"la mejor métrica no siempre es la mejor decisión de negocio",[53,5869,5871],{"id":5870},"evaluación","Evaluación",[12,5873,5874],{},"En el conjunto de prueba:",[1359,5876,5877,5880,5883],{},[1362,5878,5879],{},"9% churn real",[1362,5881,5882],{},"Modelo detectó 76% de los churners",[1362,5884,5885],{},"Falsos positivos: 18%",[12,5887,5888],{},"Simulación:",[12,5890,5891],{},"Se decide intervenir solo en usuarios con probabilidad > 0.65.",[12,5893,5894],{},"Usuarios marcados como \"riesgo alto\": 11,000",[12,5896,5897],{},"De esos:",[1359,5899,5900,5903],{},[1362,5901,5902],{},"6,800 realmente iban a cancelar",[1362,5904,5905],{},"4,200 eran falsos positivos",[12,5907,5908],{},"Costo campaña:",[74,5910,5913],{"className":5911,"code":5912,"language":2235},[2816],"11,000 × $2 = $22,000\n",[61,5914,5912],{"__ignoreMap":79},[12,5916,5917],{},"Clientes salvados (tasa de éxito campaña 40%):",[74,5919,5922],{"className":5920,"code":5921,"language":2235},[2816],"6,800 × 40% = 2,720 clientes retenidos\n",[61,5923,5921],{"__ignoreMap":79},[12,5925,5926],{},"Ingreso recuperado mensual:",[74,5928,5931],{"className":5929,"code":5930,"language":2235},[2816],"2,720 × $25 = $68,000\n",[61,5932,5930],{"__ignoreMap":79},[12,5934,5935],{},"ROI mensual:",[74,5937,5940],{"className":5938,"code":5939,"language":2235},[2816],"$68,000 - $22,000 = $46,000 beneficio neto\n",[61,5941,5939],{"__ignoreMap":79},[12,5943,5944],{},"Objetivo cumplido.",[53,5946,5948],{"id":5947},"implementación","Implementación",[12,5950,5951],{},"El modelo se desplegó como:",[1359,5953,5954,5957,5960,5963],{},[1362,5955,5956],{},"API REST en FastAPI",[1362,5958,5959],{},"Contenedor Docker",[1362,5961,5962],{},"Job nocturno que recalcula riesgo diario",[1362,5964,5965],{},"Integración con CRM para disparar campañas automáticas",[12,5967,5968],{},"Tiempo de inferencia por usuario: 12 ms.",[53,5970,5972],{"id":5971},"monitoreo-en-producción","Monitoreo en producción",[12,5974,5975],{},"Después de 4 meses:",[12,5977,5978],{},"La tasa de churn volvió a subir a 7.4%.",[12,5980,5981],{},"Se detectó:",[1359,5983,5984,5987],{},[1362,5985,5986],{},"Nuevo competidor con descuento agresivo",[1362,5988,5989],{},"Cambio en comportamiento de usuarios jóvenes",[12,5991,5992,5993,5996],{},"Se identificó ",[40,5994,5995],{},"concept drift",", es decir, el modelo ya no estaba capturando correctamente los patrones de churn debido a cambios en el mercado y en el comportamiento de los usuarios.",[12,5998,5999],{},"Se hizo retraining con datos recientes.",[12,6001,6002],{},"Nuevo modelo:",[1359,6004,6005,6008],{},[1362,6006,6007],{},"Mejoró recall a 81%",[1362,6009,6010],{},"Redujo churn nuevamente a 6.2%",[29,6012],{},[12,6014,6015,6016,6019],{},"¿Que podemos aprender de este caso? Primero, ",[40,6017,6018],{},"el modelo no era el centro — el proceso sí",". El éxito no vino de un algoritmo sofisticado, sino de un proceso bien ejecutado que incluyó:",[1359,6021,6022,6025,6028],{},[1362,6023,6024],{},"Buen EDA",[1362,6026,6027],{},"Buen feature engineering",[1362,6029,6030],{},"Definir correctamente la métrica de negocio",[12,6032,6033,6034,6037],{},"Segundo, accuracy no era la métrica correcta, aqui ya nos importaba ponerle ojo al ROI, porque no solo queríamos un modelo que fuera bueno en métricas técnicas, sino que también generara un impacto positivo en el negocio.\nY es que como ya hemos dicho, ",[40,6035,6036],{},"el modelo es parte de un sistema"," que incluye otros componentes como marketing, CRM, infraestructura, monitoreo y retraining. El éxito del proyecto depende de la integración efectiva de todos estos componentes, no solo del modelo en sí.",[12,6039,6040,6041,6044],{},"Tercero, el proyecto nunca termina, ",[40,6042,6043],{},"es un ciclo continuo",", el monitoreo y mantenimiento son tan importantes como el entrenamiento inicial, porque el entorno cambia, los usuarios cambian, el mercado cambia, y el modelo debe adaptarse para seguir siendo efectivo.",[29,6046],{},{"title":79,"searchDepth":116,"depth":116,"links":6048},[6049,6050,6051,6052,6055,6065,6066,6071,6072,6073],{"id":4479,"depth":103,"text":4480},{"id":4542,"depth":103,"text":4543},{"id":4578,"depth":103,"text":4579},{"id":4588,"depth":103,"text":4589,"children":6053},[6054],{"id":4684,"depth":116,"text":4685},{"id":4717,"depth":103,"text":4718,"children":6056},[6057,6058,6059,6060,6061,6062,6063,6064],{"id":4753,"depth":116,"text":4754},{"id":4813,"depth":116,"text":4814},{"id":4870,"depth":116,"text":4871},{"id":4920,"depth":116,"text":4921},{"id":4969,"depth":116,"text":4970},{"id":5001,"depth":116,"text":5002},{"id":5030,"depth":116,"text":5031},{"id":5053,"depth":116,"text":5054},{"id":5079,"depth":103,"text":5080},{"id":5158,"depth":103,"text":5159,"children":6067},[6068,6069,6070],{"id":5209,"depth":116,"text":5210},{"id":5258,"depth":116,"text":5259},{"id":5265,"depth":116,"text":5266},{"id":5272,"depth":103,"text":5273},{"id":5311,"depth":103,"text":5312},{"id":5445,"depth":103,"text":5446,"children":6074},[6075,6076,6077,6078,6079,6080,6081,6082,6083],{"id":5523,"depth":116,"text":5524},{"id":5581,"depth":116,"text":5582},{"id":5614,"depth":116,"text":5615},{"id":5642,"depth":116,"text":5643},{"id":5700,"depth":116,"text":4333},{"id":5767,"depth":116,"text":5768},{"id":5870,"depth":116,"text":5871},{"id":5947,"depth":116,"text":5948},{"id":5971,"depth":116,"text":5972},"2026-04-18","\u002Fblog\u002Fworkflow-machine-learning-projects\u002Fshared\u002Fworkflow.webp",{},"\u002Fblog\u002Fblog\u002Fworkflow-machine-learning-projects",{"title":24,"description":4411},{"loc":6090,"priority":4394,"lastmod":6084},"\u002Fes\u002Fblog\u002Fworkflow-machine-learning-projects","workflow-machine-learning-projects","blog\u002Fblog\u002Fworkflow-machine-learning-projects","Descubre el flujo típico de un proyecto de aprendizaje automático, desde la recopilación de datos hasta la implementación del modelo, y aprende sobre las mejores prácticas y desafíos comunes en el campo de la ciencia de datos.",[6095,6096,6097,6098],"Machine Learning","Data Science","Proyectos de ML","Flujo de trabajo","ZkFJq61zQv5OaLfXLn08N_uhSfWM-jtyyhkQNh9ycXY",{"id":6101,"title":4418,"author":7,"body":6102,"date":23455,"description":6106,"extension":4387,"image":23456,"lastmod":23455,"meta":23457,"navigation":160,"order":116,"path":23458,"seo":23459,"sitemap":23460,"slug":23462,"stem":23463,"summary":23464,"tags":23465,"__hash__":23468},"content_es\u002Fblog\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations.md",{"type":9,"value":6103,"toc":23439},[6104,6107,6114,6116,6118,6122,6125,6145,6149,6152,6706,6786,6789,6803,6806,6811,6813,6817,7026,7040,7045,7047,7051,7054,7080,7083,7088,7090,7094,7104,7107,7115,7118,7121,7596,7599,8221,8283,8394,8494,8503,8506,8577,8617,8878,8881,9219,9222,9655,9657,9936,9939,10239,10242,10618,10660,10665,10843,11431,11672,11674,11984,11987,12025,12032,12217,12219,12458,12600,13175,13412,13414,13722,13725,14329,14687,14877,15002,15104,15107,15265,15272,15674,15676,15895,15900,16489,16494,16737,17156,17161,17460,17496,17507,17509,17512,17518,17521,17524,17544,17549,17552,17674,17799,17806,17815,18265,18274,18468,18473,19099,19101,19641,19644,19649,19652,19841,19843,20398,20452,20455,20598,20605,20748,21049,21062,21065,21383,21386,22014,22016,22293,22296,22307,22310,22319,22322,22327,22602,22607,22902,22905,22909,22913,22919,22945,22949,22974,22979,22983,22990,22993,23099,23101,23219,23222,23321,23324,23333,23347,23350,23377,23381,23384],[12,6105,6106],{},"Continuamos aprendiendo sobre Machine Learning, en esta ocasión nos adentraremos en los diferentes paradigmas de aprendizaje automático y los fundamentos matemáticos que sustentan estos modelos.",[12,6108,17,6109],{},[19,6110,6113],{"href":6111,"rel":6112},"https:\u002F\u002Fderas.dev\u002Fes\u002Fblog\u002Fmachine-learning-fundamentals",[23],"Fundamentos de Aprendizaje Automático",[26,6115],{},[29,6117],{},[32,6119,6121],{"id":6120},"paradigmas-de-aprendizaje-automático","Paradigmas de Aprendizaje Automático",[12,6123,6124],{},"El machine learning NO comienza con algoritmos. EL proceso comienza con una comprension profunda del problema antes de seleccionar cualquier técnica o modelo, además de tres criterios fundamentales para determinar que enfoque  y técnicas podemos usar:",[1359,6126,6127,6133,6139],{},[1362,6128,6129,6132],{},[40,6130,6131],{},"Naturaleza de los datos",": Analizar el tipo de datos disponibles (etiquetados o no etiquetados) y su estructura.",[1362,6134,6135,6138],{},[40,6136,6137],{},"Tipo de salida esperada",": ¿Qué tipo de resultado esperamos obtener? ¿Una\ncategoría, un número continuo, o una estructura oculta?",[1362,6140,6141,6144],{},[40,6142,6143],{},"Interacción con el entorno",": ¿El modelo necesita aprender a través de la interacción con un entorno dinámico?",[53,6146,6148],{"id":6147},"aprendizaje-supervisado","Aprendizaje Supervisado",[12,6150,6151],{},"El aprendizaje supervisado requiere un conjunto de datos donde cada ejemplo de entrada X está asociado con una etiqueta o salida Y. El objetivo del modelo es aprender una función que mapee las entradas a las salidas correctas.",[12,6153,6154,6155,6559,6560,6633,6634,6705],{},"En función de esto, el conjunto de datos de entrenamiento se representa como un conjunto de pares ",[83,6156,6158,6241],{"className":6157},[2151],[83,6159,6161],{"className":6160},[2155],[2157,6162,6163],{"xmlns":2159},[2162,6164,6165,6238],{},[2165,6166,6167,6170,6172,6178,6180,6186,6188,6190,6192,6198,6200,6206,6208,6210,6212,6214,6216,6218,6220,6226,6228,6234,6236],{},[2172,6168,3610],{"stretchy":6169},"false",[2172,6171,187],{"stretchy":6169},[2175,6173,6174,6176],{},[2178,6175,1640],{},[2182,6177,1161],{},[2172,6179,256],{"separator":2204},[2175,6181,6182,6184],{},[2178,6183,3972],{},[2182,6185,1161],{},[2172,6187,534],{"stretchy":6169},[2172,6189,256],{"separator":2204},[2172,6191,187],{"stretchy":6169},[2175,6193,6194,6196],{},[2178,6195,1640],{},[2182,6197,1149],{},[2172,6199,256],{"separator":2204},[2175,6201,6202,6204],{},[2178,6203,3972],{},[2182,6205,1149],{},[2172,6207,534],{"stretchy":6169},[2172,6209,256],{"separator":2204},[2178,6211,133],{"mathvariant":689},[2178,6213,133],{"mathvariant":689},[2178,6215,133],{"mathvariant":689},[2172,6217,256],{"separator":2204},[2172,6219,187],{"stretchy":6169},[2175,6221,6222,6224],{},[2178,6223,1640],{},[2178,6225,313],{},[2172,6227,256],{"separator":2204},[2175,6229,6230,6232],{},[2178,6231,3972],{},[2178,6233,313],{},[2172,6235,534],{"stretchy":6169},[2172,6237,3619],{"stretchy":6169},[2214,6239,6240],{"encoding":2216},"\\{(x_1, y_1), (x_2, y_2), ..., (x_n, y_n)\\}",[83,6242,6244],{"className":6243,"ariaHidden":2204},[2221],[83,6245,6247,6251,6256,6297,6301,6305,6347,6351,6354,6357,6360,6400,6403,6406,6446,6449,6452,6455,6459,6462,6465,6468,6509,6512,6515,6555],{"className":6246},[2225],[83,6248],{"className":6249,"style":6250},[2229],"height:1em;vertical-align:-0.25em;",[83,6252,6255],{"className":6253},[6254],"mopen","{(",[83,6257,6259,6262],{"className":6258},[2234],[83,6260,1640],{"className":6261},[2234,2264],[83,6263,6265],{"className":6264},[2269],[83,6266,6268,6289],{"className":6267},[2273,2274],[83,6269,6271,6286],{"className":6270},[2278],[83,6272,6274],{"className":6273,"style":2283},[2282],[83,6275,6277,6280],{"style":6276},"top:-2.55em;margin-left:0em;margin-right:0.05em;",[83,6278],{"className":6279,"style":2291},[2290],[83,6281,6283],{"className":6282},[2295,2296,2297,2298],[83,6284,1161],{"className":6285},[2234,2298],[83,6287,2306],{"className":6288},[2305],[83,6290,6292],{"className":6291},[2278],[83,6293,6295],{"className":6294,"style":2313},[2282],[83,6296],{},[83,6298,256],{"className":6299},[6300],"mpunct",[83,6302],{"className":6303,"style":6304},[2242],"margin-right:0.1667em;",[83,6306,6308,6312],{"className":6307},[2234],[83,6309,3972],{"className":6310,"style":6311},[2234,2264],"margin-right:0.0359em;",[83,6313,6315],{"className":6314},[2269],[83,6316,6318,6339],{"className":6317},[2273,2274],[83,6319,6321,6336],{"className":6320},[2278],[83,6322,6324],{"className":6323,"style":2283},[2282],[83,6325,6327,6330],{"style":6326},"top:-2.55em;margin-left:-0.0359em;margin-right:0.05em;",[83,6328],{"className":6329,"style":2291},[2290],[83,6331,6333],{"className":6332},[2295,2296,2297,2298],[83,6334,1161],{"className":6335},[2234,2298],[83,6337,2306],{"className":6338},[2305],[83,6340,6342],{"className":6341},[2278],[83,6343,6345],{"className":6344,"style":2313},[2282],[83,6346],{},[83,6348,534],{"className":6349},[6350],"mclose",[83,6352,256],{"className":6353},[6300],[83,6355],{"className":6356,"style":6304},[2242],[83,6358,187],{"className":6359},[6254],[83,6361,6363,6366],{"className":6362},[2234],[83,6364,1640],{"className":6365},[2234,2264],[83,6367,6369],{"className":6368},[2269],[83,6370,6372,6392],{"className":6371},[2273,2274],[83,6373,6375,6389],{"className":6374},[2278],[83,6376,6378],{"className":6377,"style":2283},[2282],[83,6379,6380,6383],{"style":6276},[83,6381],{"className":6382,"style":2291},[2290],[83,6384,6386],{"className":6385},[2295,2296,2297,2298],[83,6387,1149],{"className":6388},[2234,2298],[83,6390,2306],{"className":6391},[2305],[83,6393,6395],{"className":6394},[2278],[83,6396,6398],{"className":6397,"style":2313},[2282],[83,6399],{},[83,6401,256],{"className":6402},[6300],[83,6404],{"className":6405,"style":6304},[2242],[83,6407,6409,6412],{"className":6408},[2234],[83,6410,3972],{"className":6411,"style":6311},[2234,2264],[83,6413,6415],{"className":6414},[2269],[83,6416,6418,6438],{"className":6417},[2273,2274],[83,6419,6421,6435],{"className":6420},[2278],[83,6422,6424],{"className":6423,"style":2283},[2282],[83,6425,6426,6429],{"style":6326},[83,6427],{"className":6428,"style":2291},[2290],[83,6430,6432],{"className":6431},[2295,2296,2297,2298],[83,6433,1149],{"className":6434},[2234,2298],[83,6436,2306],{"className":6437},[2305],[83,6439,6441],{"className":6440},[2278],[83,6442,6444],{"className":6443,"style":2313},[2282],[83,6445],{},[83,6447,534],{"className":6448},[6350],[83,6450,256],{"className":6451},[6300],[83,6453],{"className":6454,"style":6304},[2242],[83,6456,6458],{"className":6457},[2234],"...",[83,6460,256],{"className":6461},[6300],[83,6463],{"className":6464,"style":6304},[2242],[83,6466,187],{"className":6467},[6254],[83,6469,6471,6474],{"className":6470},[2234],[83,6472,1640],{"className":6473},[2234,2264],[83,6475,6477],{"className":6476},[2269],[83,6478,6480,6501],{"className":6479},[2273,2274],[83,6481,6483,6498],{"className":6482},[2278],[83,6484,6487],{"className":6485,"style":6486},[2282],"height:0.1514em;",[83,6488,6489,6492],{"style":6276},[83,6490],{"className":6491,"style":2291},[2290],[83,6493,6495],{"className":6494},[2295,2296,2297,2298],[83,6496,313],{"className":6497},[2234,2264,2298],[83,6499,2306],{"className":6500},[2305],[83,6502,6504],{"className":6503},[2278],[83,6505,6507],{"className":6506,"style":2313},[2282],[83,6508],{},[83,6510,256],{"className":6511},[6300],[83,6513],{"className":6514,"style":6304},[2242],[83,6516,6518,6521],{"className":6517},[2234],[83,6519,3972],{"className":6520,"style":6311},[2234,2264],[83,6522,6524],{"className":6523},[2269],[83,6525,6527,6547],{"className":6526},[2273,2274],[83,6528,6530,6544],{"className":6529},[2278],[83,6531,6533],{"className":6532,"style":6486},[2282],[83,6534,6535,6538],{"style":6326},[83,6536],{"className":6537,"style":2291},[2290],[83,6539,6541],{"className":6540},[2295,2296,2297,2298],[83,6542,313],{"className":6543},[2234,2264,2298],[83,6545,2306],{"className":6546},[2305],[83,6548,6550],{"className":6549},[22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donde ",[83,6561,6563,6582],{"className":6562},[2151],[83,6564,6566],{"className":6565},[2155],[2157,6567,6568],{"xmlns":2159},[2162,6569,6570,6579],{},[2165,6571,6572],{},[2175,6573,6574,6576],{},[2178,6575,1640],{},[2178,6577,6578],{},"i",[2214,6580,6581],{"encoding":2216},"x_i",[83,6583,6585],{"className":6584,"ariaHidden":2204},[2221],[83,6586,6588,6592],{"className":6587},[2225],[83,6589],{"className":6590,"style":6591},[2229],"height:0.5806em;vertical-align:-0.15em;",[83,6593,6595,6598],{"className":6594},[2234],[83,6596,1640],{"className":6597},[2234,2264],[83,6599,6601],{"className":6600},[2269],[83,6602,6604,6625],{"className":6603},[2273,2274],[83,6605,6607,6622],{"className":6606},[2278],[83,6608,6611],{"className":6609,"style":6610},[2282],"height:0.3117em;",[83,6612,6613,6616],{"style":6276},[83,6614],{"className":6615,"style":2291},[2290],[83,6617,6619],{"className":6618},[2295,2296,2297,2298],[83,6620,6578],{"className":6621},[2234,2264,2298],[83,6623,2306],{"className":6624},[2305],[83,6626,6628],{"className":6627},[2278],[83,6629,6631],{"className":6630,"style":2313},[2282],[83,6632],{}," es la entrada y ",[83,6635,6637,6655],{"className":6636},[2151],[83,6638,6640],{"className":6639},[2155],[2157,6641,6642],{"xmlns":2159},[2162,6643,6644,6652],{},[2165,6645,6646],{},[2175,6647,6648,6650],{},[2178,6649,3972],{},[2178,6651,6578],{},[2214,6653,6654],{"encoding":2216},"y_i",[83,6656,6658],{"className":6657,"ariaHidden":2204},[2221],[83,6659,6661,6665],{"className":6660},[2225],[83,6662],{"className":6663,"style":6664},[2229],"height:0.625em;vertical-align:-0.1944em;",[83,6666,6668,6671],{"className":6667},[2234],[83,6669,3972],{"className":6670,"style":6311},[2234,2264],[83,6672,6674],{"className":6673},[2269],[83,6675,6677,6697],{"className":6676},[2273,2274],[83,6678,6680,6694],{"className":6679},[2278],[83,6681,6683],{"className":6682,"style":6610},[2282],[83,6684,6685,6688],{"style":6326},[83,6686],{"className":6687,"style":2291},[2290],[83,6689,6691],{"className":6690},[2295,2296,2297,2298],[83,6692,6578],{"className":6693},[2234,2264,2298],[83,6695,2306],{"className":6696},[2305],[83,6698,6700],{"className":6699},[2278],[83,6701,6703],{"className":6702,"style":2313},[2282],[83,6704],{}," es la etiqueta correspondiente. El modelo de aprendizaje supervisado intenta encontrar una función f que pueda predecir la salida Y a partir de la entrada X:",[83,6707,6709],{"className":6708},[2147],[83,6710,6712,6736],{"className":6711},[2151],[83,6713,6715],{"className":6714},[2155],[2157,6716,6717],{"xmlns":2159,"display":2160},[2162,6718,6719,6733],{},[2165,6720,6721,6723,6725,6727,6730],{},[2178,6722,3604],{},[2172,6724,624],{},[2178,6726,3417],{},[2172,6728,6729],{},"→",[2178,6731,6732],{},"Y",[2214,6734,6735],{"encoding":2216},"f: X \\rightarrow Y",[83,6737,6739,6758,6777],{"className":6738,"ariaHidden":2204},[2221],[83,6740,6742,6745,6749,6752,6755],{"className":6741},[2225],[83,6743],{"className":6744,"style":2257},[2229],[83,6746,3604],{"className":6747,"style":6748},[2234,2264],"margin-right:0.1076em;",[83,6750],{"className":6751,"style":2243},[2242],[83,6753,624],{"className":6754},[2247],[83,6756],{"className":6757,"style":2243},[2242],[83,6759,6761,6764,6768,6771,6774],{"className":6760},[2225],[83,6762],{"className":6763,"style":2230},[2229],[83,6765,3417],{"className":6766,"style":6767},[2234,2264],"margin-right:0.0785em;",[83,6769],{"className":6770,"style":2243},[2242],[83,6772,6729],{"className":6773},[2247],[83,6775],{"className":6776,"style":2243},[2242],[83,6778,6780,6783],{"className":6779},[2225],[83,6781],{"className":6782,"style":2230},[2229],[83,6784,6732],{"className":6785,"style":2319},[2234,2264],[12,6787,6788],{},"Dependiendo del tipo de salida, el aprendizaje supervisado se puede dividir en:",[1359,6790,6791,6797],{},[1362,6792,6793,6796],{},[40,6794,6795],{},"Clasificación",": Cuando la salida Y es una categoría discreta (es decir, un valor categórico). Por ejemplo, clasificar si una imagen contiene un gato o un perro, si un número es par o impar, o si un correo electrónico es spam o no spam.",[1362,6798,6799,6802],{},[40,6800,6801],{},"Regresión",": Cuando la salida Y es un valor continuo (es decir, un número real). Por ejemplo, hacer una predicción de las ventas futuras basándose en datos históricos, predecir el precio de una casa basándose en sus características, o estimar la temperatura de una ciudad en función de factores climáticos.",[12,6804,6805],{},"Una regla que nos puede servir para detectar si un problema es de clasificación o regresión es, si la respuesta es \"¿Cuánto?\" entonces es un problema de regresión, pero si la respuesta es \"¿Cuál?\" entonces es un problema de clasificación.",[2073,6807,6808],{},[12,6809,6810],{},"Objetivo: Aprender una función que mapee las entradas a las salidas correctas, minimizando el error entre las predicciones del modelo.",[29,6812],{},[53,6814,6816],{"id":6815},"aprendizaje-no-supervisado","Aprendizaje No Supervisado",[12,6818,6819,6820,7025],{},"En el aprendizaje no supervisado, el modelo recibe solo las entradas X sin etiquetas asociadas: ",[83,6821,6823,6869],{"className":6822},[2151],[83,6824,6826],{"className":6825},[2155],[2157,6827,6828],{"xmlns":2159},[2162,6829,6830,6866],{},[2165,6831,6832,6834,6840,6842,6848,6850,6852,6854,6856,6858,6864],{},[2172,6833,3610],{"stretchy":6169},[2175,6835,6836,6838],{},[2178,6837,1640],{},[2182,6839,1161],{},[2172,6841,256],{"separator":2204},[2175,6843,6844,6846],{},[2178,6845,1640],{},[2182,6847,1149],{},[2172,6849,256],{"separator":2204},[2178,6851,133],{"mathvariant":689},[2178,6853,133],{"mathvariant":689},[2178,6855,133],{"mathvariant":689},[2172,6857,256],{"separator":2204},[2175,6859,6860,6862],{},[2178,6861,1640],{},[2178,6863,313],{},[2172,6865,3619],{"stretchy":6169},[2214,6867,6868],{"encoding":2216},"\\{x_1, x_2, ..., x_n\\}",[83,6870,6872],{"className":6871,"ariaHidden":2204},[2221],[83,6873,6875,6878,6881,6921,6924,6927,6967,6970,6973,6976,6979,6982,7022],{"className":6874},[2225],[83,6876],{"className":6877,"style":6250},[2229],[83,6879,3610],{"className":6880},[6254],[83,6882,6884,6887],{"className":6883},[2234],[83,6885,1640],{"className":6886},[2234,2264],[83,6888,6890],{"className":6889},[2269],[83,6891,6893,6913],{"className":6892},[2273,2274],[83,6894,6896,6910],{"className":6895},[2278],[83,6897,6899],{"className":6898,"style":2283},[2282],[83,6900,6901,6904],{"style":6276},[83,6902],{"className":6903,"style":2291},[2290],[83,6905,6907],{"className":6906},[2295,2296,2297,2298],[83,6908,1161],{"className":6909},[2234,2298],[83,6911,2306],{"className":6912},[2305],[83,6914,6916],{"className":6915},[2278],[83,6917,6919],{"className":6918,"style":2313},[2282],[83,6920],{},[83,6922,256],{"className":6923},[6300],[83,6925],{"className":6926,"style":6304},[2242],[83,6928,6930,6933],{"className":6929},[2234],[83,6931,1640],{"className":6932},[2234,2264],[83,6934,6936],{"className":6935},[2269],[83,6937,6939,6959],{"className":6938},[2273,2274],[83,6940,6942,6956],{"className":6941},[2278],[83,6943,6945],{"className":6944,"style":2283},[2282],[83,6946,6947,6950],{"style":6276},[83,6948],{"className":6949,"style":2291},[2290],[83,6951,6953],{"className":6952},[2295,2296,2297,2298],[83,6954,1149],{"className":6955},[2234,2298],[83,6957,2306],{"className":6958},[2305],[83,6960,6962],{"className":6961},[2278],[83,6963,6965],{"className":6964,"style":2313},[2282],[83,6966],{},[83,6968,256],{"className":6969},[6300],[83,6971],{"className":6972,"style":6304},[2242],[83,6974,6458],{"className":6975},[2234],[83,6977,256],{"className":6978},[6300],[83,6980],{"className":6981,"style":6304},[2242],[83,6983,6985,6988],{"className":6984},[2234],[83,6986,1640],{"className":6987},[2234,2264],[83,6989,6991],{"className":6990},[2269],[83,6992,6994,7014],{"className":6993},[2273,2274],[83,6995,6997,7011],{"className":6996},[2278],[83,6998,7000],{"className":6999,"style":6486},[2282],[83,7001,7002,7005],{"style":6276},[83,7003],{"className":7004,"style":2291},[2290],[83,7006,7008],{"className":7007},[2295,2296,2297,2298],[83,7009,313],{"className":7010},[2234,2264,2298],[83,7012,2306],{"className":7013},[2305],[83,7015,7017],{"className":7016},[2278],[83,7018,7020],{"className":7019,"style":2313},[2282],[83,7021],{},[83,7023,3619],{"className":7024},[6350],". Lo que se busca es encontrar patrones o estructuras subyacentes en los datos.\nAlgunos ejemplos de técnicas de aprendizaje no supervisado incluyen:",[1359,7027,7028,7034],{},[1362,7029,7030,7033],{},[40,7031,7032],{},"Clustering",": Agrupar datos similares en clusters. Por ejemplo, segmentar clientes en grupos basados en sus comportamientos de compra.",[1362,7035,7036,7039],{},[40,7037,7038],{},"Reducción de Dimensionalidad",": Reducir el número de variables en un conjunto de datos mientras se conserva la mayor cantidad de información posible. Por ejemplo, usar PCA (Análisis de Componentes Principales) para visualizar datos en 2D o 3D.",[2073,7041,7042],{},[12,7043,7044],{},"Objetivo: Encontrar patrones o estructuras subyacentes en los datos sin etiquetas, como agrupamientos o representaciones más compactas.",[29,7046],{},[53,7048,7050],{"id":7049},"aprendizaje-por-refuerzo","Aprendizaje por Refuerzo",[12,7052,7053],{},"El aprendizaje por refuerzo se basa en la idea de que un agente aprende a tomar decisiones mediante la interacción con un entorno. El agente recibe recompensas o castigos en función de las acciones que toma, y su objetivo es maximizar la recompensa acumulada a lo largo del tiempo.\nEn este paradigma, el agente aprende una política de acción que le permite tomar decisiones óptimas en función del estado actual del entorno. Un ejemplo clásico de aprendizaje por refuerzo es el juego de ajedrez, donde el agente aprende a jugar mejor a medida que juega más partidas y recibe retroalimentación sobre sus movimientos.",[1406,7055,7056,7062,7068,7074],{},[1362,7057,7058,7061],{},[40,7059,7060],{},"Agente",": El sistema que toma decisiones.",[1362,7063,7064,7067],{},[40,7065,7066],{},"Entorno",": El mundo con el que el agente interactúa.",[1362,7069,7070,7073],{},[40,7071,7072],{},"Recompensa",": La retroalimentación que el agente recibe después de tomar una acción.",[1362,7075,7076,7079],{},[40,7077,7078],{},"Política",": La estrategia que el agente sigue para tomar decisiones.",[12,7081,7082],{},"Sus aplicaciones incluyen juegos, robótica y sistemas de recomendación.",[2073,7084,7085],{},[12,7086,7087],{},"Objetivo: Aprender a tomar decisiones óptimas mediante la interacción con un entorno, maximizando la recompensa acumulada a lo largo del tiempo.",[29,7089],{},[32,7091,7093],{"id":7092},"fundamentos-matemáticos","Fundamentos Matemáticos",[12,7095,7096,7097,7100,7101,133],{},"Es importante entender que el aprendizaje automático se basa en conceptos de álgebra lineal, cálculo, probabilidad y estadística. Estos fundamentos son esenciales para comprender cómo ",[40,7098,7099],{},"funcionan"," los modelos y cómo se ",[40,7102,7103],{},"optimizan",[53,7105,6801],{"id":7106},"regresión",[2073,7108,7109],{},[12,7110,7111,7112,133],{},"Utilizado en el ",[40,7113,7114],{},"aprendizaje supervisado",[12,7116,7117],{},"¿Qué es un problema de regresión? Es un tipo de problema donde el objetivo es predecir un valor continuo encontrando la mejor línea (o plano) que se ajuste a los datos. Ya hablamos de ejemplos de aplicación como el cálculo de precios, ventas, etc.",[12,7119,7120],{},"La forma mas simple de regresión es la regresión lineal, que se puede expresar matemáticamente como:",[83,7122,7124],{"className":7123},[2147],[83,7125,7127,7204],{"className":7126},[2151],[83,7128,7130],{"className":7129},[2155],[2157,7131,7132],{"xmlns":2159,"display":2160},[2162,7133,7134,7201],{},[2165,7135,7136,7138,7140,7146,7148,7154,7160,7162,7168,7174,7176,7178,7180,7182,7184,7190,7196,7198],{},[2178,7137,3972],{},[2172,7139,229],{},[2175,7141,7142,7144],{},[2178,7143,2180],{},[2182,7145,411],{},[2172,7147,2186],{},[2175,7149,7150,7152],{},[2178,7151,2180],{},[2182,7153,1161],{},[2175,7155,7156,7158],{},[2178,7157,1640],{},[2182,7159,1161],{},[2172,7161,2186],{},[2175,7163,7164,7166],{},[2178,7165,2180],{},[2182,7167,1149],{},[2175,7169,7170,7172],{},[2178,7171,1640],{},[2182,7173,1149],{},[2172,7175,2186],{},[2178,7177,133],{"mathvariant":689},[2178,7179,133],{"mathvariant":689},[2178,7181,133],{"mathvariant":689},[2172,7183,2186],{},[2175,7185,7186,7188],{},[2178,7187,2180],{},[2178,7189,12],{},[2175,7191,7192,7194],{},[2178,7193,1640],{},[2178,7195,12],{},[2172,7197,2186],{},[2178,7199,7200],{},"ϵ",[2214,7202,7203],{"encoding":2216},"y = \\beta_0 + \\beta_1 x_1 + \\beta_2 x_2 + ... + \\beta_p x_p + 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es la variable dependiente (lo que queremos predecir).",[1362,7633,7634,7830],{},[83,7635,7637,7679],{"className":7636},[2151],[83,7638,7640],{"className":7639},[2155],[2157,7641,7642],{"xmlns":2159},[2162,7643,7644,7676],{},[2165,7645,7646,7652,7654,7660,7662,7664,7666,7668,7670],{},[2175,7647,7648,7650],{},[2178,7649,1640],{},[2182,7651,1161],{},[2172,7653,256],{"separator":2204},[2175,7655,7656,7658],{},[2178,7657,1640],{},[2182,7659,1149],{},[2172,7661,256],{"separator":2204},[2178,7663,133],{"mathvariant":689},[2178,7665,133],{"mathvariant":689},[2178,7667,133],{"mathvariant":689},[2172,7669,256],{"separator":2204},[2175,7671,7672,7674],{},[2178,7673,1640],{},[2178,7675,12],{},[2214,7677,7678],{"encoding":2216},"x_1, x_2, ..., x_p",[83,7680,7682],{"className":7681,"ariaHidden":2204},[2221],[83,7683,7685,7689,7729,7732,7735,7775,7778,7781,7784,7787,7790],{"className":7684},[2225],[83,7686],{"className":7687,"style":7688},[2229],"height:0.7167em;vertical-align:-0.2861em;",[83,7690,7692,7695],{"className":7691},[2234],[83,7693,1640],{"className":7694},[2234,2264],[83,7696,7698],{"className":7697},[2269],[83,7699,7701,7721],{"className":7700},[2273,2274],[83,7702,7704,7718],{"className":7703},[2278],[83,7705,7707],{"className":7706,"style":2283},[2282],[83,7708,7709,7712],{"style":6276},[83,7710],{"className":7711,"style":2291},[2290],[83,7713,7715],{"className":7714},[2295,2296,2297,2298],[83,7716,1161],{"className":7717},[2234,2298],[83,7719,2306],{"className":7720},[2305],[83,7722,7724],{"className":7723},[2278],[83,7725,7727],{"className":7726,"style":2313},[2282],[83,7728],{},[83,7730,256],{"className":7731},[6300],[83,7733],{"className":7734,"style":6304},[2242],[83,7736,7738,7741],{"className":7737},[2234],[83,7739,1640],{"className":7740},[2234,2264],[83,7742,7744],{"className":7743},[2269],[83,7745,7747,7767],{"className":7746},[2273,2274],[83,7748,7750,7764],{"className":7749},[2278],[83,7751,7753],{"className":7752,"style":2283},[2282],[83,7754,7755,7758],{"style":6276},[83,7756],{"className":7757,"style":2291},[2290],[83,7759,7761],{"className":7760},[2295,2296,2297,2298],[83,7762,1149],{"className":7763},[2234,2298],[83,7765,2306],{"className":7766},[2305],[83,7768,7770],{"className":7769},[2278],[83,7771,7773],{"className":7772,"style":2313},[2282],[83,7774],{},[83,7776,256],{"className":7777},[6300],[83,7779],{"className":7780,"style":6304},[2242],[83,7782,6458],{"className":7783},[2234],[83,7785,256],{"className":7786},[6300],[83,7788],{"className":7789,"style":6304},[2242],[83,7791,7793,7796],{"className":7792},[2234],[83,7794,1640],{"className":7795},[2234,2264],[83,7797,7799],{"className":7798},[2269],[83,7800,7802,7822],{"className":7801},[2273,2274],[83,7803,7805,7819],{"className":7804},[2278],[83,7806,7808],{"className":7807,"style":6486},[2282],[83,7809,7810,7813],{"style":6276},[83,7811],{"className":7812,"style":2291},[2290],[83,7814,7816],{"className":7815},[2295,2296,2297,2298],[83,7817,12],{"className":7818},[2234,2264,2298],[83,7820,2306],{"className":7821},[2305],[83,7823,7825],{"className":7824},[2278],[83,7826,7828],{"className":7827,"style":7534},[2282],[83,7829],{}," son las variables independientes (las características).",[1362,7832,7833,7903,7904,7932,7933,7961],{},[83,7834,7836,7854],{"className":7835},[2151],[83,7837,7839],{"className":7838},[2155],[2157,7840,7841],{"xmlns":2159},[2162,7842,7843,7851],{},[2165,7844,7845],{},[2175,7846,7847,7849],{},[2178,7848,2180],{},[2182,7850,411],{},[2214,7852,7853],{"encoding":2216},"\\beta_0",[83,7855,7857],{"className":7856,"ariaHidden":2204},[2221],[83,7858,7860,7863],{"className":7859},[2225],[83,7861],{"className":7862,"style":2257},[2229],[83,7864,7866,7869],{"className":7865},[2234],[83,7867,2180],{"className":7868,"style":2265},[2234,2264],[83,7870,7872],{"className":7871},[2269],[83,7873,7875,7895],{"className":7874},[2273,2274],[83,7876,7878,7892],{"className":7877},[2278],[83,7879,7881],{"className":7880,"style":2283},[2282],[83,7882,7883,7886],{"style":2286},[83,7884],{"className":7885,"style":2291},[2290],[83,7887,7889],{"className":7888},[2295,2296,2297,2298],[83,7890,411],{"className":7891},[2234,2298],[83,7893,2306],{"className":7894},[2305],[83,7896,7898],{"className":7897},[2278],[83,7899,7901],{"className":7900,"style":2313},[2282],[83,7902],{}," es la intersección (el valor de ",[83,7905,7907,7920],{"className":7906},[2151],[83,7908,7910],{"className":7909},[2155],[2157,7911,7912],{"xmlns":2159},[2162,7913,7914,7918],{},[2165,7915,7916],{},[2178,7917,3972],{},[2214,7919,3972],{"encoding":2216},[83,7921,7923],{"className":7922,"ariaHidden":2204},[2221],[83,7924,7926,7929],{"className":7925},[2225],[83,7927],{"className":7928,"style":6664},[2229],[83,7930,3972],{"className":7931,"style":6311},[2234,2264]," cuando todas las ",[83,7934,7936,7949],{"className":7935},[2151],[83,7937,7939],{"className":7938},[2155],[2157,7940,7941],{"xmlns":2159},[2162,7942,7943,7947],{},[2165,7944,7945],{},[2178,7946,1640],{},[2214,7948,1640],{"encoding":2216},[83,7950,7952],{"className":7951,"ariaHidden":2204},[2221],[83,7953,7955,7958],{"className":7954},[2225],[83,7956],{"className":7957,"style":7592},[2229],[83,7959,1640],{"className":7960},[2234,2264]," son 0).",[1362,7963,7964,8159],{},[83,7965,7967,8009],{"className":7966},[2151],[83,7968,7970],{"className":7969},[2155],[2157,7971,7972],{"xmlns":2159},[2162,7973,7974,8006],{},[2165,7975,7976,7982,7984,7990,7992,7994,7996,7998,8000],{},[2175,7977,7978,7980],{},[2178,7979,2180],{},[2182,7981,1161],{},[2172,7983,256],{"separator":2204},[2175,7985,7986,7988],{},[2178,7987,2180],{},[2182,7989,1149],{},[2172,7991,256],{"separator":2204},[2178,7993,133],{"mathvariant":689},[2178,7995,133],{"mathvariant":689},[2178,7997,133],{"mathvariant":689},[2172,7999,256],{"separator":2204},[2175,8001,8002,8004],{},[2178,8003,2180],{},[2178,8005,12],{},[2214,8007,8008],{"encoding":2216},"\\beta_1, \\beta_2, ..., \\beta_p",[83,8010,8012],{"className":8011,"ariaHidden":2204},[2221],[83,8013,8015,8018,8058,8061,8064,8104,8107,8110,8113,8116,8119],{"className":8014},[2225],[83,8016],{"className":8017,"style":7495},[2229],[83,8019,8021,8024],{"className":8020},[2234],[83,8022,2180],{"className":8023,"style":2265},[2234,2264],[83,8025,8027],{"className":8026},[2269],[83,8028,8030,8050],{"className":8029},[2273,2274],[83,8031,8033,8047],{"className":8032},[2278],[83,8034,8036],{"className":8035,"style":2283},[2282],[83,8037,8038,8041],{"style":2286},[83,8039],{"className":8040,"style":2291},[2290],[83,8042,8044],{"className":8043},[2295,2296,2297,2298],[83,8045,1161],{"className":8046},[2234,2298],[83,8048,2306],{"className":8049},[2305],[83,8051,8053],{"className":8052},[2278],[83,8054,8056],{"className":8055,"style":2313},[2282],[83,8057],{},[83,8059,256],{"className":8060},[6300],[83,8062],{"className":8063,"style":6304},[2242],[83,8065,8067,8070],{"className":8066},[2234],[83,8068,2180],{"className":8069,"style":2265},[2234,2264],[83,8071,8073],{"className":8072},[2269],[83,8074,8076,8096],{"className":8075},[2273,2274],[83,8077,8079,8093],{"className":8078},[2278],[83,8080,8082],{"className":8081,"style":2283},[2282],[83,8083,8084,8087],{"style":2286},[83,8085],{"className":8086,"style":2291},[2290],[83,8088,8090],{"className":8089},[2295,2296,2297,2298],[83,8091,1149],{"className":8092},[2234,2298],[83,8094,2306],{"className":8095},[2305],[83,8097,8099],{"className":8098},[2278],[83,8100,8102],{"className":8101,"style":2313},[2282],[83,8103],{},[83,8105,256],{"className":8106},[6300],[83,8108],{"className":8109,"style":6304},[2242],[83,8111,6458],{"className":8112},[2234],[83,8114,256],{"className":8115},[6300],[83,8117],{"className":8118,"style":6304},[2242],[83,8120,8122,8125],{"className":8121},[2234],[83,8123,2180],{"className":8124,"style":2265},[2234,2264],[83,8126,8128],{"className":8127},[2269],[83,8129,8131,8151],{"className":8130},[2273,2274],[83,8132,8134,8148],{"className":8133},[2278],[83,8135,8137],{"className":8136,"style":6486},[2282],[83,8138,8139,8142],{"style":2286},[83,8140],{"className":8141,"style":2291},[2290],[83,8143,8145],{"className":8144},[2295,2296,2297,2298],[83,8146,12],{"className":8147},[2234,2264,2298],[83,8149,2306],{"className":8150},[2305],[83,8152,8154],{"className":8153},[2278],[83,8155,8157],{"className":8156,"style":7534},[2282],[83,8158],{}," son los coeficientes que representan la influencia de cada característica en la variable dependiente.",[1362,8161,8162,8191,8192,8220],{},[83,8163,8165,8179],{"className":8164},[2151],[83,8166,8168],{"className":8167},[2155],[2157,8169,8170],{"xmlns":2159},[2162,8171,8172,8176],{},[2165,8173,8174],{},[2178,8175,7200],{},[2214,8177,8178],{"encoding":2216},"\\epsilon",[83,8180,8182],{"className":8181,"ariaHidden":2204},[2221],[83,8183,8185,8188],{"className":8184},[2225],[83,8186],{"className":8187,"style":7592},[2229],[83,8189,7200],{"className":8190},[2234,2264]," es el valor de error o ruido, que representa la variabilidad no explicada por el modelo, es decir, lo que afecta a ",[83,8193,8195,8208],{"className":8194},[2151],[83,8196,8198],{"className":8197},[2155],[2157,8199,8200],{"xmlns":2159},[2162,8201,8202,8206],{},[2165,8203,8204],{},[2178,8205,3972],{},[2214,8207,3972],{"encoding":2216},[83,8209,8211],{"className":8210,"ariaHidden":2204},[2221],[83,8212,8214,8217],{"className":8213},[2225],[83,8215],{"className":8216,"style":6664},[2229],[83,8218,3972],{"className":8219,"style":6311},[2234,2264]," pero no está incluido en las variables independientes.",[12,8222,8223,8224,8253,8254,8282],{},"El objetivo del modelo de regresión es encontrar los valores de los coeficientes ",[83,8225,8227,8241],{"className":8226},[2151],[83,8228,8230],{"className":8229},[2155],[2157,8231,8232],{"xmlns":2159},[2162,8233,8234,8238],{},[2165,8235,8236],{},[2178,8237,2180],{},[2214,8239,8240],{"encoding":2216},"\\beta",[83,8242,8244],{"className":8243,"ariaHidden":2204},[2221],[83,8245,8247,8250],{"className":8246},[2225],[83,8248],{"className":8249,"style":2257},[2229],[83,8251,2180],{"className":8252,"style":2265},[2234,2264]," que minimicen la diferencia entre las predicciones del modelo y los valores reales de ",[83,8255,8257,8270],{"className":8256},[2151],[83,8258,8260],{"className":8259},[2155],[2157,8261,8262],{"xmlns":2159},[2162,8263,8264,8268],{},[2165,8265,8266],{},[2178,8267,3972],{},[2214,8269,3972],{"encoding":2216},[83,8271,8273],{"className":8272,"ariaHidden":2204},[2221],[83,8274,8276,8279],{"className":8275},[2225],[83,8277],{"className":8278,"style":6664},[2229],[83,8280,3972],{"className":8281,"style":6311},[2234,2264],". Esto se puede lograr utilizando técnicas como el método de mínimos cuadrados.",[12,8284,8285,8286,8289,8290,8328,8329,8362,8363,8393],{},"El ",[40,8287,8288],{},"intercepto"," se representa como el primer elemento del vector de coeficientes ",[83,8291,8293,8308],{"className":8292},[2151],[83,8294,8296],{"className":8295},[2155],[2157,8297,8298],{"xmlns":2159},[2162,8299,8300,8305],{},[2165,8301,8302],{},[2178,8303,2180],{"mathvariant":8304},"bold-italic",[2214,8306,8307],{"encoding":2216},"\\boldsymbol{\\beta}",[83,8309,8311],{"className":8310,"ariaHidden":2204},[2221],[83,8312,8314,8317],{"className":8313},[2225],[83,8315],{"className":8316,"style":2257},[2229],[83,8318,8320],{"className":8319},[2234],[83,8321,8323],{"className":8322},[2234],[83,8324,2180],{"className":8325,"style":8327},[2234,8326],"boldsymbol","margin-right:0.034em;",", y es el valor de ",[83,8330,8332,8347],{"className":8331},[2151],[83,8333,8335],{"className":8334},[2155],[2157,8336,8337],{"xmlns":2159},[2162,8338,8339,8344],{},[2165,8340,8341],{},[2178,8342,3972],{"mathvariant":8343},"bold",[2214,8345,8346],{"encoding":2216},"\\mathbf{y}",[83,8348,8350],{"className":8349,"ariaHidden":2204},[2221],[83,8351,8353,8357],{"className":8352},[2225],[83,8354],{"className":8355,"style":8356},[2229],"height:0.6389em;vertical-align:-0.1944em;",[83,8358,3972],{"className":8359,"style":8361},[2234,8360],"mathbf","margin-right:0.016em;"," cuando todas las variables independientes en ",[83,8364,8366,8380],{"className":8365},[2151],[83,8367,8369],{"className":8368},[2155],[2157,8370,8371],{"xmlns":2159},[2162,8372,8373,8377],{},[2165,8374,8375],{},[2178,8376,3417],{"mathvariant":8343},[2214,8378,8379],{"encoding":2216},"\\mathbf{X}",[83,8381,8383],{"className":8382,"ariaHidden":2204},[2221],[83,8384,8386,8390],{"className":8385},[2225],[83,8387],{"className":8388,"style":8389},[2229],"height:0.6861em;",[83,8391,3417],{"className":8392},[2234,8360]," son cero, es decir, representa el punto de la línea de regresión donde cruza el eje Y.",[12,8395,8396,8397,8400,8401,8435,8436,8464,8465,8493],{},"La ",[40,8398,8399],{},"pendiente"," se representa por los coeficientes restantes en el vector ",[83,8402,8404,8417],{"className":8403},[2151],[83,8405,8407],{"className":8406},[2155],[2157,8408,8409],{"xmlns":2159},[2162,8410,8411,8415],{},[2165,8412,8413],{},[2178,8414,2180],{"mathvariant":8304},[2214,8416,8307],{"encoding":2216},[83,8418,8420],{"className":8419,"ariaHidden":2204},[2221],[83,8421,8423,8426],{"className":8422},[2225],[83,8424],{"className":8425,"style":2257},[2229],[83,8427,8429],{"className":8428},[2234],[83,8430,8432],{"className":8431},[2234],[83,8433,2180],{"className":8434,"style":8327},[2234,8326],", y cada coeficiente indica la cantidad de cambio en la variable dependiente ",[83,8437,8439,8452],{"className":8438},[2151],[83,8440,8442],{"className":8441},[2155],[2157,8443,8444],{"xmlns":2159},[2162,8445,8446,8450],{},[2165,8447,8448],{},[2178,8449,3972],{"mathvariant":8343},[2214,8451,8346],{"encoding":2216},[83,8453,8455],{"className":8454,"ariaHidden":2204},[2221],[83,8456,8458,8461],{"className":8457},[2225],[83,8459],{"className":8460,"style":8356},[2229],[83,8462,3972],{"className":8463,"style":8361},[2234,8360]," por cada unidad de cambio en la variable independiente correspondiente en ",[83,8466,8468,8481],{"className":8467},[2151],[83,8469,8471],{"className":8470},[2155],[2157,8472,8473],{"xmlns":2159},[2162,8474,8475,8479],{},[2165,8476,8477],{},[2178,8478,3417],{"mathvariant":8343},[2214,8480,8379],{"encoding":2216},[83,8482,8484],{"className":8483,"ariaHidden":2204},[2221],[83,8485,8487,8490],{"className":8486},[2225],[83,8488],{"className":8489,"style":8389},[2229],[83,8491,3417],{"className":8492},[2234,8360],", manteniendo constantes las demás variables independientes.\nGráficamente podemos verlo de la siguiente manera:",[12,8495,8496,8500],{},[1882,8497],{"alt":8498,"src":8499},"Gráfico de regresión lineal","\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations\u002Fshared\u002Fregression-model.webp",[1887,8501,8502],{},"Gráfico de Regresión Lineal",[12,8504,8505],{},"Cada punto negro representa un dato de entrenamiento, y la línea roja el modelo.",[12,8507,8508,8509,8512,8513,8547,8548,8576],{},"Lo importante aquí es entender que ",[40,8510,8511],{},"el objetivo principal"," es encontrar los valores de los coeficientes ",[83,8514,8516,8529],{"className":8515},[2151],[83,8517,8519],{"className":8518},[2155],[2157,8520,8521],{"xmlns":2159},[2162,8522,8523,8527],{},[2165,8524,8525],{},[2178,8526,2180],{"mathvariant":8304},[2214,8528,8307],{"encoding":2216},[83,8530,8532],{"className":8531,"ariaHidden":2204},[2221],[83,8533,8535,8538],{"className":8534},[2225],[83,8536],{"className":8537,"style":2257},[2229],[83,8539,8541],{"className":8540},[2234],[83,8542,8544],{"className":8543},[2234],[83,8545,2180],{"className":8546,"style":8327},[2234,8326]," que hagan que las predicciones ",[83,8549,8551,8564],{"className":8550},[2151],[83,8552,8554],{"className":8553},[2155],[2157,8555,8556],{"xmlns":2159},[2162,8557,8558,8562],{},[2165,8559,8560],{},[2178,8561,3972],{"mathvariant":8343},[2214,8563,8346],{"encoding":2216},[83,8565,8567],{"className":8566,"ariaHidden":2204},[2221],[83,8568,8570,8573],{"className":8569},[2225],[83,8571],{"className":8572,"style":8356},[2229],[83,8574,3972],{"className":8575,"style":8361},[2234,8360]," (la línea roja) sean lo más cercanas a los valores reales.",[12,8578,8579,8580,8616],{},"Es decir, no se busca predecir con exactitud, siempre (en la realidad) habrá un error o diferencia entre lo que el modelo predice y lo que realmente ocurre. EL término ",[83,8581,8583,8597],{"className":8582},[2151],[83,8584,8586],{"className":8585},[2155],[2157,8587,8588],{"xmlns":2159},[2162,8589,8590,8594],{},[2165,8591,8592],{},[2178,8593,7200],{"mathvariant":8304},[2214,8595,8596],{"encoding":2216},"\\boldsymbol{\\epsilon}",[83,8598,8600],{"className":8599,"ariaHidden":2204},[2221],[83,8601,8603,8607],{"className":8602},[2225],[83,8604],{"className":8605,"style":8606},[2229],"height:0.4444em;",[83,8608,8610],{"className":8609},[2234],[83,8611,8613],{"className":8612},[2234],[83,8614,7200],{"className":8615},[2234,8326]," es la diferencia entre los valores predichos por el modelo y los valores reales:",[83,8618,8620],{"className":8619},[2147],[83,8621,8623,8665],{"className":8622},[2151],[83,8624,8626],{"className":8625},[2155],[2157,8627,8628],{"xmlns":2159,"display":2160},[2162,8629,8630,8662],{},[2165,8631,8632,8640,8642,8648,8651],{},[2178,8633,8634],{},[2175,8635,8636,8638],{},[2178,8637,7200],{"mathvariant":8304},[2178,8639,6578],{"mathvariant":8304},[2172,8641,229],{},[2175,8643,8644,8646],{},[2178,8645,3972],{"mathvariant":8343},[2178,8647,6578],{"mathvariant":8343},[2172,8649,8650],{},"−",[2202,8652,8653,8659],{"accent":2204},[2175,8654,8655,8657],{},[2178,8656,3972],{"mathvariant":8343},[2178,8658,6578],{"mathvariant":8343},[2172,8660,8661],{},"^",[2214,8663,8664],{"encoding":2216},"\\boldsymbol{\\epsilon _i} = \\mathbf{y_i} - \\hat{\\mathbf{y_i}}",[83,8666,8668,8731,8789],{"className":8667,"ariaHidden":2204},[2221],[83,8669,8671,8675,8722,8725,8728],{"className":8670},[2225],[83,8672],{"className":8673,"style":8674},[2229],"height:0.5944em;vertical-align:-0.15em;",[83,8676,8678],{"className":8677},[2234],[83,8679,8681],{"className":8680},[2234],[83,8682,8684,8687],{"className":8683},[2234],[83,8685,7200],{"className":8686},[2234,8326],[83,8688,8690],{"className":8689},[2269],[83,8691,8693,8714],{"className":8692},[2273,2274],[83,8694,8696,8711],{"className":8695},[2278],[83,8697,8700],{"className":8698,"style":8699},[2282],"height:0.3353em;",[83,8701,8702,8705],{"style":6276},[83,8703],{"className":8704,"style":2291},[2290],[83,8706,8708],{"className":8707},[2295,2296,2297,2298],[83,8709,6578],{"className":8710},[2234,8326,2298],[83,8712,2306],{"className":8713},[2305],[83,8715,8717],{"className":8716},[2278],[83,8718,8720],{"className":8719,"style":2313},[2282],[83,8721],{},[83,8723],{"className":8724,"style":2243},[2242],[83,8726,229],{"className":8727},[2247],[83,8729],{"className":8730,"style":2243},[2242],[83,8732,8734,8738,8780,8783,8786],{"className":8733},[2225],[83,8735],{"className":8736,"style":8737},[2229],"height:0.7778em;vertical-align:-0.1944em;",[83,8739,8741,8744],{"className":8740},[2234],[83,8742,3972],{"className":8743,"style":8361},[2234,8360],[83,8745,8747],{"className":8746},[2269],[83,8748,8750,8772],{"className":8749},[2273,2274],[83,8751,8753,8769],{"className":8752},[2278],[83,8754,8757],{"className":8755,"style":8756},[2282],"height:0.3361em;",[83,8758,8760,8763],{"style":8759},"top:-2.55em;margin-left:-0.016em;margin-right:0.05em;",[83,8761],{"className":8762,"style":2291},[2290],[83,8764,8766],{"className":8765},[2295,2296,2297,2298],[83,8767,6578],{"className":8768},[2234,8360,2298],[83,8770,2306],{"className":8771},[2305],[83,8773,8775],{"className":8774},[2278],[83,8776,8778],{"className":8777,"style":2313},[2282],[83,8779],{},[83,8781],{"className":8782,"style":2319},[2242],[83,8784,8650],{"className":8785},[2323],[83,8787],{"className":8788,"style":2319},[2242],[83,8790,8792,8796],{"className":8791},[2225],[83,8793],{"className":8794,"style":8795},[2229],"height:0.9023em;vertical-align:-0.1944em;",[83,8797,8799],{"className":8798},[2234,2398],[83,8800,8802,8869],{"className":8801},[2273,2274],[83,8803,8805,8866],{"className":8804},[2278],[83,8806,8809,8854],{"className":8807,"style":8808},[2282],"height:0.7079em;",[83,8810,8811,8814],{"style":2410},[83,8812],{"className":8813,"style":2414},[2290],[83,8815,8817,8820],{"className":8816},[2234],[83,8818,3972],{"className":8819,"style":8361},[2234,8360],[83,8821,8823],{"className":8822},[2269],[83,8824,8826,8846],{"className":8825},[2273,2274],[83,8827,8829,8843],{"className":8828},[2278],[83,8830,8832],{"className":8831,"style":8756},[2282],[83,8833,8834,8837],{"style":8759},[83,8835],{"className":8836,"style":2291},[2290],[83,8838,8840],{"className":8839},[2295,2296,2297,2298],[83,8841,6578],{"className":8842},[2234,8360,2298],[83,8844,2306],{"className":8845},[2305],[83,8847,8849],{"className":8848},[2278],[83,8850,8852],{"className":8851,"style":2313},[2282],[83,8853],{},[83,8855,8857,8860],{"style":8856},"top:-3.0134em;",[83,8858],{"className":8859,"style":2414},[2290],[83,8861,8863],{"className":8862,"style":2427},[2426],[83,8864,8661],{"className":8865},[2234],[83,8867,2306],{"className":8868},[2305],[83,8870,8872],{"className":8871},[2278],[83,8873,8876],{"className":8874,"style":8875},[2282],"height:0.1944em;",[83,8877],{},[12,8879,8880],{},"Que también se puede expresar como:",[83,8882,8884],{"className":8883},[2147],[83,8885,8887,8943],{"className":8886},[2151],[83,8888,8890],{"className":8889},[2155],[2157,8891,8892],{"xmlns":2159,"display":2160},[2162,8893,8894,8940],{},[2165,8895,8896,8904,8906,8912,8914,8916,8924,8926,8932,8938],{},[2178,8897,8898],{},[2175,8899,8900,8902],{},[2178,8901,7200],{"mathvariant":8304},[2178,8903,6578],{"mathvariant":8304},[2172,8905,229],{},[2175,8907,8908,8910],{},[2178,8909,3972],{"mathvariant":8343},[2178,8911,6578],{"mathvariant":8343},[2172,8913,8650],{},[2172,8915,187],{"stretchy":6169},[2178,8917,8918],{},[2175,8919,8920,8922],{},[2178,8921,2180],{"mathvariant":8304},[2182,8923,411],{"mathvariant":8343},[2172,8925,2186],{},[2175,8927,8928,8930],{},[2178,8929,2180],{},[2182,8931,1161],{},[2175,8933,8934,8936],{},[2178,8935,1640],{},[2178,8937,6578],{},[2172,8939,534],{"stretchy":6169},[2214,8941,8942],{"encoding":2216},"\\boldsymbol{\\epsilon _i} = \\mathbf{y_i} - (\\boldsymbol{\\beta_0} + \\beta_1 x_{i})",[83,8944,8946,9007,9062,9127],{"className":8945,"ariaHidden":2204},[2221],[83,8947,8949,8952,8998,9001,9004],{"className":8948},[2225],[83,8950],{"className":8951,"style":8674},[2229],[83,8953,8955],{"className":8954},[2234],[83,8956,8958],{"className":8957},[2234],[83,8959,8961,8964],{"className":8960},[2234],[83,8962,7200],{"className":8963},[2234,8326],[83,8965,8967],{"className":8966},[2269],[83,8968,8970,8990],{"className":8969},[2273,2274],[83,8971,8973,8987],{"className":8972},[2278],[83,8974,8976],{"className":8975,"style":8699},[2282],[83,8977,8978,8981],{"style":6276},[83,8979],{"className":8980,"style":2291},[2290],[83,8982,8984],{"className":8983},[2295,2296,2297,2298],[83,8985,6578],{"className":8986},[2234,8326,2298],[83,8988,2306],{"className":8989},[2305],[83,8991,8993],{"className":8992},[2278],[83,8994,8996],{"className":8995,"style":2313},[2282],[83,8997],{},[83,8999],{"className":9000,"style":2243},[2242],[83,9002,229],{"className":9003},[2247],[83,9005],{"className":9006,"style":2243},[2242],[83,9008,9010,9013,9053,9056,9059],{"className":9009},[2225],[83,9011],{"className":9012,"style":8737},[2229],[83,9014,9016,9019],{"className":9015},[2234],[83,9017,3972],{"className":9018,"style":8361},[2234,8360],[83,9020,9022],{"className":9021},[2269],[83,9023,9025,9045],{"className":9024},[2273,2274],[83,9026,9028,9042],{"className":9027},[2278],[83,9029,9031],{"className":9030,"style":8756},[2282],[83,9032,9033,9036],{"style":8759},[83,9034],{"className":9035,"style":2291},[2290],[83,9037,9039],{"className":9038},[2295,2296,2297,2298],[83,9040,6578],{"className":9041},[2234,8360,2298],[83,9043,2306],{"className":9044},[2305],[83,9046,9048],{"className":9047},[2278],[83,9049,9051],{"className":9050,"style":2313},[2282],[83,9052],{},[83,9054],{"className":9055,"style":2319},[2242],[83,9057,8650],{"className":9058},[2323],[83,9060],{"className":9061,"style":2319},[2242],[83,9063,9065,9068,9071,9118,9121,9124],{"className":9064},[2225],[83,9066],{"className":9067,"style":6250},[2229],[83,9069,187],{"className":9070},[6254],[83,9072,9074],{"className":9073},[2234],[83,9075,9077],{"className":9076},[2234],[83,9078,9080,9083],{"className":9079},[2234],[83,9081,2180],{"className":9082,"style":8327},[2234,8326],[83,9084,9086],{"className":9085},[2269],[83,9087,9089,9110],{"className":9088},[2273,2274],[83,9090,9092,9107],{"className":9091},[2278],[83,9093,9095],{"className":9094,"style":2283},[2282],[83,9096,9098,9101],{"style":9097},"top:-2.55em;margin-left:-0.034em;margin-right:0.05em;",[83,9099],{"className":9100,"style":2291},[2290],[83,9102,9104],{"className":9103},[2295,2296,2297,2298],[83,9105,411],{"className":9106},[2234,8360,2298],[83,9108,2306],{"className":9109},[2305],[83,9111,9113],{"className":9112},[2278],[83,9114,9116],{"className":9115,"style":2313},[2282],[83,9117],{},[83,9119],{"className":9120,"style":2319},[2242],[83,9122,2186],{"className":9123},[2323],[83,9125],{"className":9126,"style":2319},[2242],[83,9128,9130,9133,9173,9216],{"className":9129},[2225],[83,9131],{"className":9132,"style":6250},[2229],[83,9134,9136,9139],{"className":9135},[2234],[83,9137,2180],{"className":9138,"style":2265},[2234,2264],[83,9140,9142],{"className":9141},[2269],[83,9143,9145,9165],{"className":9144},[2273,2274],[83,9146,9148,9162],{"className":9147},[2278],[83,9149,9151],{"className":9150,"style":2283},[2282],[83,9152,9153,9156],{"style":2286},[83,9154],{"className":9155,"style":2291},[2290],[83,9157,9159],{"className":9158},[2295,2296,2297,2298],[83,9160,1161],{"className":9161},[2234,2298],[83,9163,2306],{"className":9164},[2305],[83,9166,9168],{"className":9167},[2278],[83,9169,9171],{"className":9170,"style":2313},[2282],[83,9172],{},[83,9174,9176,9179],{"className":9175},[2234],[83,9177,1640],{"className":9178},[2234,2264],[83,9180,9182],{"className":9181},[2269],[83,9183,9185,9208],{"className":9184},[2273,2274],[83,9186,9188,9205],{"className":9187},[2278],[83,9189,9191],{"className":9190,"style":6610},[2282],[83,9192,9193,9196],{"style":6276},[83,9194],{"className":9195,"style":2291},[2290],[83,9197,9199],{"className":9198},[2295,2296,2297,2298],[83,9200,9202],{"className":9201},[2234,2298],[83,9203,6578],{"className":9204},[2234,2264,2298],[83,9206,2306],{"className":9207},[2305],[83,9209,9211],{"className":9210},[2278],[83,9212,9214],{"className":9213,"style":2313},[2282],[83,9215],{},[83,9217,534],{"className":9218},[6350],[12,9220,9221],{},"Para medir el error podemos utilizar una función de pérdida. En el caso de la regresión lineal, una función de pérdida comúnmente utilizada es el error cuadrático medio (MSE, por sus siglas en inglés), que se define como:",[83,9223,9225],{"className":9224},[2147],[83,9226,9228,9300],{"className":9227},[2151],[83,9229,9231],{"className":9230},[2155],[2157,9232,9233],{"xmlns":2159,"display":2160},[2162,9234,9235,9297],{},[2165,9236,9237,9240,9243,9246,9248,9255,9271,9273,9279,9281,9291],{},[2178,9238,9239],{},"M",[2178,9241,9242],{},"S",[2178,9244,9245],{},"E",[2172,9247,229],{},[9249,9250,9251,9253],"mfrac",{},[2182,9252,1161],{},[2178,9254,313],{},[9256,9257,9258,9261,9269],"munderover",{},[2172,9259,9260],{},"∑",[2165,9262,9263,9265,9267],{},[2178,9264,6578],{},[2172,9266,229],{},[2182,9268,1161],{},[2178,9270,313],{},[2172,9272,187],{"stretchy":6169},[2175,9274,9275,9277],{},[2178,9276,3972],{},[2178,9278,6578],{},[2172,9280,8650],{},[2202,9282,9283,9289],{"accent":2204},[2175,9284,9285,9287],{},[2178,9286,3972],{},[2178,9288,6578],{},[2172,9290,8661],{},[3702,9292,9293,9295],{},[2172,9294,534],{"stretchy":6169},[2182,9296,1149],{},[2214,9298,9299],{"encoding":2216},"MSE = \\frac{1}{n} \\sum_{i=1}^{n} (y_i - \\hat{y_i})^2",[83,9301,9303,9329,9538],{"className":9302,"ariaHidden":2204},[2221],[83,9304,9306,9309,9313,9317,9320,9323,9326],{"className":9305},[2225],[83,9307],{"className":9308,"style":2230},[2229],[83,9310,9239],{"className":9311,"style":9312},[2234,2264],"margin-right:0.109em;",[83,9314,9242],{"className":9315,"style":9316},[2234,2264],"margin-right:0.0576em;",[83,9318,9245],{"className":9319,"style":9316},[2234,2264],[83,9321],{"className":9322,"style":2243},[2242],[83,9324,229],{"className":9325},[2247],[83,9327],{"className":9328,"style":2243},[2242],[83,9330,9332,9336,9406,9409,9486,9489,9529,9532,9535],{"className":9331},[2225],[83,9333],{"className":9334,"style":9335},[2229],"height:2.9291em;vertical-align:-1.2777em;",[83,9337,9339,9343,9403],{"className":9338},[2234],[83,9340],{"className":9341},[6254,9342],"nulldelimiter",[83,9344,9346],{"className":9345},[9249],[83,9347,9349,9394],{"className":9348},[2273,2274],[83,9350,9352,9391],{"className":9351},[2278],[83,9353,9356,9368,9379],{"className":9354,"style":9355},[2282],"height:1.3214em;",[83,9357,9359,9362],{"style":9358},"top:-2.314em;",[83,9360],{"className":9361,"style":2414},[2290],[83,9363,9365],{"className":9364},[2234],[83,9366,313],{"className":9367},[2234,2264],[83,9369,9371,9374],{"style":9370},"top:-3.23em;",[83,9372],{"className":9373,"style":2414},[2290],[83,9375],{"className":9376,"style":9378},[9377],"frac-line","border-bottom-width:0.04em;",[83,9380,9382,9385],{"style":9381},"top:-3.677em;",[83,9383],{"className":9384,"style":2414},[2290],[83,9386,9388],{"className":9387},[2234],[83,9389,1161],{"className":9390},[2234],[83,9392,2306],{"className":9393},[2305],[83,9395,9397],{"className":9396},[2278],[83,9398,9401],{"className":9399,"style":9400},[2282],"height:0.686em;",[83,9402],{},[83,9404],{"className":9405},[6350,9342],[83,9407],{"className":9408,"style":6304},[2242],[83,9410,9414],{"className":9411},[9412,9413],"mop","op-limits",[83,9415,9417,9477],{"className":9416},[2273,2274],[83,9418,9420,9474],{"className":9419},[2278],[83,9421,9424,9446,9459],{"className":9422,"style":9423},[2282],"height:1.6514em;",[83,9425,9427,9431],{"style":9426},"top:-1.8723em;margin-left:0em;",[83,9428],{"className":9429,"style":9430},[2290],"height:3.05em;",[83,9432,9434],{"className":9433},[2295,2296,2297,2298],[83,9435,9437,9440,9443],{"className":9436},[2234,2298],[83,9438,6578],{"className":9439},[2234,2264,2298],[83,9441,229],{"className":9442},[2247,2298],[83,9444,1161],{"className":9445},[2234,2298],[83,9447,9449,9452],{"style":9448},"top:-3.05em;",[83,9450],{"className":9451,"style":9430},[2290],[83,9453,9454],{},[83,9455,9260],{"className":9456},[9412,9457,9458],"op-symbol","large-op",[83,9460,9462,9465],{"style":9461},"top:-4.3em;margin-left:0em;",[83,9463],{"className":9464,"style":9430},[2290],[83,9466,9468],{"className":9467},[2295,2296,2297,2298],[83,9469,9471],{"className":9470},[2234,2298],[83,9472,313],{"className":9473},[2234,2264,2298],[83,9475,2306],{"className":9476},[2305],[83,9478,9480],{"className":9479},[2278],[83,9481,9484],{"className":9482,"style":9483},[2282],"height:1.2777em;",[83,9485],{},[83,9487,187],{"className":9488},[6254],[83,9490,9492,9495],{"className":9491},[2234],[83,9493,3972],{"className":9494,"style":6311},[2234,2264],[83,9496,9498],{"className":9497},[2269],[83,9499,9501,9521],{"className":9500},[2273,2274],[83,9502,9504,9518],{"className":9503},[2278],[83,9505,9507],{"className":9506,"style":6610},[2282],[83,9508,9509,9512],{"style":6326},[83,9510],{"className":9511,"style":2291},[2290],[83,9513,9515],{"className":9514},[2295,2296,2297,2298],[83,9516,6578],{"className":9517},[2234,2264,2298],[83,9519,2306],{"className":9520},[2305],[83,9522,9524],{"className":9523},[2278],[83,9525,9527],{"className":9526,"style":2313},[2282],[83,9528],{},[83,9530],{"className":9531,"style":2319},[2242],[83,9533,8650],{"className":9534},[2323],[83,9536],{"className":9537,"style":2319},[2242],[83,9539,9541,9545,9624],{"className":9540},[2225],[83,9542],{"className":9543,"style":9544},[2229],"height:1.1141em;vertical-align:-0.25em;",[83,9546,9548],{"className":9547},[2234,2398],[83,9549,9551,9616],{"className":9550},[2273,2274],[83,9552,9554,9613],{"className":9553},[2278],[83,9555,9557,9602],{"className":9556,"style":2388},[2282],[83,9558,9559,9562],{"style":2410},[83,9560],{"className":9561,"style":2414},[2290],[83,9563,9565,9568],{"className":9564},[2234],[83,9566,3972],{"className":9567,"style":6311},[2234,2264],[83,9569,9571],{"className":9570},[2269],[83,9572,9574,9594],{"className":9573},[2273,2274],[83,9575,9577,9591],{"className":9576},[2278],[83,9578,9580],{"className":9579,"style":6610},[2282],[83,9581,9582,9585],{"style":6326},[83,9583],{"className":9584,"style":2291},[2290],[83,9586,9588],{"className":9587},[2295,2296,2297,2298],[83,9589,6578],{"className":9590},[2234,2264,2298],[83,9592,2306],{"className":9593},[2305],[83,9595,9597],{"className":9596},[2278],[83,9598,9600],{"className":9599,"style":2313},[2282],[83,9601],{},[83,9603,9604,9607],{"style":2410},[83,9605],{"className":9606,"style":2414},[2290],[83,9608,9610],{"className":9609,"style":2427},[2426],[83,9611,8661],{"className":9612},[2234],[83,9614,2306],{"className":9615},[2305],[83,9617,9619],{"className":9618},[2278],[83,9620,9622],{"className":9621,"style":8875},[2282],[83,9623],{},[83,9625,9627,9630],{"className":9626},[6350],[83,9628,534],{"className":9629},[6350],[83,9631,9633],{"className":9632},[2269],[83,9634,9636],{"className":9635},[2273],[83,9637,9639],{"className":9638},[2278],[83,9640,9643],{"className":9641,"style":9642},[2282],"height:0.8641em;",[83,9644,9646,9649],{"style":9645},"top:-3.113em;margin-right:0.05em;",[83,9647],{"className":9648,"style":2291},[2290],[83,9650,9652],{"className":9651},[2295,2296,2297,2298],[83,9653,1149],{"className":9654},[2234,2298],[12,9656,7598],{},[1359,9658,9659,9690,9791],{},[1362,9660,9661,9689],{},[83,9662,9664,9677],{"className":9663},[2151],[83,9665,9667],{"className":9666},[2155],[2157,9668,9669],{"xmlns":2159},[2162,9670,9671,9675],{},[2165,9672,9673],{},[2178,9674,313],{},[2214,9676,313],{"encoding":2216},[83,9678,9680],{"className":9679,"ariaHidden":2204},[2221],[83,9681,9683,9686],{"className":9682},[2225],[83,9684],{"className":9685,"style":7592},[2229],[83,9687,313],{"className":9688},[2234,2264]," es el número de ejemplos en el conjunto de datos.",[1362,9691,9692,9761,9762,133],{},[83,9693,9695,9712],{"className":9694},[2151],[83,9696,9698],{"className":9697},[2155],[2157,9699,9700],{"xmlns":2159},[2162,9701,9702,9710],{},[2165,9703,9704],{},[2175,9705,9706,9708],{},[2178,9707,3972],{},[2178,9709,6578],{},[2214,9711,6654],{"encoding":2216},[83,9713,9715],{"className":9714,"ariaHidden":2204},[2221],[83,9716,9718,9721],{"className":9717},[2225],[83,9719],{"className":9720,"style":6664},[2229],[83,9722,9724,9727],{"className":9723},[2234],[83,9725,3972],{"className":9726,"style":6311},[2234,2264],[83,9728,9730],{"className":9729},[2269],[83,9731,9733,9753],{"className":9732},[2273,2274],[83,9734,9736,9750],{"className":9735},[2278],[83,9737,9739],{"className":9738,"style":6610},[2282],[83,9740,9741,9744],{"style":6326},[83,9742],{"className":9743,"style":2291},[2290],[83,9745,9747],{"className":9746},[2295,2296,2297,2298],[83,9748,6578],{"className":9749},[2234,2264,2298],[83,9751,2306],{"className":9752},[2305],[83,9754,9756],{"className":9755},[2278],[83,9757,9759],{"className":9758,"style":2313},[2282],[83,9760],{}," es el valor real de la variable dependiente para el ejemplo ",[83,9763,9765,9778],{"className":9764},[2151],[83,9766,9768],{"className":9767},[2155],[2157,9769,9770],{"xmlns":2159},[2162,9771,9772,9776],{},[2165,9773,9774],{},[2178,9775,6578],{},[2214,9777,6578],{"encoding":2216},[83,9779,9781],{"className":9780,"ariaHidden":2204},[2221],[83,9782,9784,9788],{"className":9783},[2225],[83,9785],{"className":9786,"style":9787},[2229],"height:0.6595em;",[83,9789,6578],{"className":9790},[2234,2264],[1362,9792,9793,9907,9908,133],{},[83,9794,9796,9818],{"className":9795},[2151],[83,9797,9799],{"className":9798},[2155],[2157,9800,9801],{"xmlns":2159},[2162,9802,9803,9815],{},[2165,9804,9805],{},[2175,9806,9807,9813],{},[2202,9808,9809,9811],{"accent":2204},[2178,9810,3972],{},[2172,9812,8661],{},[2178,9814,6578],{},[2214,9816,9817],{"encoding":2216},"\\hat{y}_i",[83,9819,9821],{"className":9820,"ariaHidden":2204},[2221],[83,9822,9824,9827],{"className":9823},[2225],[83,9825],{"className":9826,"style":2257},[2229],[83,9828,9830,9873],{"className":9829},[2234],[83,9831,9833],{"className":9832},[2234,2398],[83,9834,9836,9865],{"className":9835},[2273,2274],[83,9837,9839,9862],{"className":9838},[2278],[83,9840,9842,9850],{"className":9841,"style":2388},[2282],[83,9843,9844,9847],{"style":2410},[83,9845],{"className":9846,"style":2414},[2290],[83,9848,3972],{"className":9849,"style":6311},[2234,2264],[83,9851,9852,9855],{"style":2410},[83,9853],{"className":9854,"style":2414},[2290],[83,9856,9859],{"className":9857,"style":9858},[2426],"left:-0.1944em;",[83,9860,8661],{"className":9861},[2234],[83,9863,2306],{"className":9864},[2305],[83,9866,9868],{"className":9867},[2278],[83,9869,9871],{"className":9870,"style":8875},[2282],[83,9872],{},[83,9874,9876],{"className":9875},[2269],[83,9877,9879,9899],{"className":9878},[2273,2274],[83,9880,9882,9896],{"className":9881},[2278],[83,9883,9885],{"className":9884,"style":6610},[2282],[83,9886,9887,9890],{"style":6326},[83,9888],{"className":9889,"style":2291},[2290],[83,9891,9893],{"className":9892},[2295,2296,2297,2298],[83,9894,6578],{"className":9895},[2234,2264,2298],[83,9897,2306],{"className":9898},[2305],[83,9900,9902],{"className":9901},[2278],[83,9903,9905],{"className":9904,"style":2313},[2282],[83,9906],{}," es la predicción del modelo para el ejemplo ",[83,9909,9911,9924],{"className":9910},[2151],[83,9912,9914],{"className":9913},[2155],[2157,9915,9916],{"xmlns":2159},[2162,9917,9918,9922],{},[2165,9919,9920],{},[2178,9921,6578],{},[2214,9923,6578],{"encoding":2216},[83,9925,9927],{"className":9926,"ariaHidden":2204},[2221],[83,9928,9930,9933],{"className":9929},[2225],[83,9931],{"className":9932,"style":9787},[2229],[83,9934,6578],{"className":9935},[2234,2264],[12,9937,9938],{},"Minimizar el MSE es equivalente a minimizar la suma de errores cuadrados:",[83,9940,9942],{"className":9941},[2147],[83,9943,9945,9997],{"className":9944},[2151],[83,9946,9948],{"className":9947},[2155],[2157,9949,9950],{"xmlns":2159,"display":2160},[2162,9951,9952,9994],{},[2165,9953,9954,9968,9970,9976,9978,9988],{},[9256,9955,9956,9958,9966],{},[2172,9957,9260],{},[2165,9959,9960,9962,9964],{},[2178,9961,6578],{},[2172,9963,229],{},[2182,9965,1161],{},[2178,9967,313],{},[2172,9969,187],{"stretchy":6169},[2175,9971,9972,9974],{},[2178,9973,3972],{},[2178,9975,6578],{},[2172,9977,8650],{},[2202,9979,9980,9986],{"accent":2204},[2175,9981,9982,9984],{},[2178,9983,3972],{},[2178,9985,6578],{},[2172,9987,8661],{},[3702,9989,9990,9992],{},[2172,9991,534],{"stretchy":6169},[2182,9993,1149],{},[2214,9995,9996],{"encoding":2216},"\\sum_{i=1}^{n} (y_i - \\hat{y_i})^2",[83,9998,10000,10125],{"className":9999,"ariaHidden":2204},[2221],[83,10001,10003,10006,10073,10076,10116,10119,10122],{"className":10002},[2225],[83,10004],{"className":10005,"style":9335},[2229],[83,10007,10009],{"className":10008},[9412,9413],[83,10010,10012,10065],{"className":10011},[2273,2274],[83,10013,10015,10062],{"className":10014},[2278],[83,10016,10018,10038,10048],{"className":10017,"style":9423},[2282],[83,10019,10020,10023],{"style":9426},[83,10021],{"className":10022,"style":9430},[2290],[83,10024,10026],{"className":10025},[2295,2296,2297,2298],[83,10027,10029,10032,10035],{"className":10028},[2234,2298],[83,10030,6578],{"className":10031},[2234,2264,2298],[83,10033,229],{"className":10034},[2247,2298],[83,10036,1161],{"className":10037},[2234,2298],[83,10039,10040,10043],{"style":9448},[83,10041],{"className":10042,"style":9430},[2290],[83,10044,10045],{},[83,10046,9260],{"className":10047},[9412,9457,9458],[83,10049,10050,10053],{"style":9461},[83,10051],{"className":10052,"style":9430},[2290],[83,10054,10056],{"className":10055},[2295,2296,2297,2298],[83,10057,10059],{"className":10058},[2234,2298],[83,10060,313],{"className":10061},[2234,2264,2298],[83,10063,2306],{"className":10064},[2305],[83,10066,10068],{"className":10067},[2278],[83,10069,10071],{"className":10070,"style":9483},[2282],[83,10072],{},[83,10074,187],{"className":10075},[6254],[83,10077,10079,10082],{"className":10078},[2234],[83,10080,3972],{"className":10081,"style":6311},[2234,2264],[83,10083,10085],{"className":10084},[2269],[83,10086,10088,10108],{"className":10087},[2273,2274],[83,10089,10091,10105],{"className":10090},[2278],[83,10092,10094],{"className":10093,"style":6610},[2282],[83,10095,10096,10099],{"style":6326},[83,10097],{"className":10098,"style":2291},[2290],[83,10100,10102],{"className":10101},[2295,2296,2297,2298],[83,10103,6578],{"className":10104},[2234,2264,2298],[83,10106,2306],{"className":10107},[2305],[83,10109,10111],{"className":10110},[2278],[83,10112,10114],{"className":10113,"style":2313},[2282],[83,10115],{},[83,10117],{"className":10118,"style":2319},[2242],[83,10120,8650],{"className":10121},[2323],[83,10123],{"className":10124,"style":2319},[2242],[83,10126,10128,10131,10210],{"className":10127},[2225],[83,10129],{"className":10130,"style":9544},[2229],[83,10132,10134],{"className":10133},[2234,2398],[83,10135,10137,10202],{"className":10136},[2273,2274],[83,10138,10140,10199],{"className":10139},[2278],[83,10141,10143,10188],{"className":10142,"style":2388},[2282],[83,10144,10145,10148],{"style":2410},[83,10146],{"className":10147,"style":2414},[2290],[83,10149,10151,10154],{"className":10150},[2234],[83,10152,3972],{"className":10153,"style":6311},[2234,2264],[83,10155,10157],{"className":10156},[2269],[83,10158,10160,10180],{"className":10159},[2273,2274],[83,10161,10163,10177],{"className":10162},[2278],[83,10164,10166],{"className":10165,"style":6610},[2282],[83,10167,10168,10171],{"style":6326},[83,10169],{"className":10170,"style":2291},[2290],[83,10172,10174],{"className":10173},[2295,2296,2297,2298],[83,10175,6578],{"className":10176},[2234,2264,2298],[83,10178,2306],{"className":10179},[2305],[83,10181,10183],{"className":10182},[2278],[83,10184,10186],{"className":10185,"style":2313},[2282],[83,10187],{},[83,10189,10190,10193],{"style":2410},[83,10191],{"className":10192,"style":2414},[2290],[83,10194,10196],{"className":10195,"style":2427},[2426],[83,10197,8661],{"className":10198},[2234],[83,10200,2306],{"className":10201},[2305],[83,10203,10205],{"className":10204},[2278],[83,10206,10208],{"className":10207,"style":8875},[2282],[83,10209],{},[83,10211,10213,10216],{"className":10212},[6350],[83,10214,534],{"className":10215},[6350],[83,10217,10219],{"className":10218},[2269],[83,10220,10222],{"className":10221},[2273],[83,10223,10225],{"className":10224},[2278],[83,10226,10228],{"className":10227,"style":9642},[2282],[83,10229,10230,10233],{"style":9645},[83,10231],{"className":10232,"style":2291},[2290],[83,10234,10236],{"className":10235},[2295,2296,2297,2298],[83,10237,1149],{"className":10238},[2234,2298],[12,10240,10241],{},"O también:",[83,10243,10245],{"className":10244},[2147],[83,10246,10248,10314],{"className":10247},[2151],[83,10249,10251],{"className":10250},[2155],[2157,10252,10253],{"xmlns":2159,"display":2160},[2162,10254,10255,10311],{},[2165,10256,10257,10271,10273,10279,10281,10283,10289,10291,10297,10303,10305],{},[9256,10258,10259,10261,10269],{},[2172,10260,9260],{},[2165,10262,10263,10265,10267],{},[2178,10264,6578],{},[2172,10266,229],{},[2182,10268,1161],{},[2178,10270,313],{},[2172,10272,187],{"stretchy":6169},[2175,10274,10275,10277],{},[2178,10276,3972],{},[2178,10278,6578],{},[2172,10280,8650],{},[2172,10282,187],{"stretchy":6169},[2175,10284,10285,10287],{},[2178,10286,2180],{},[2182,10288,411],{},[2172,10290,2186],{},[2175,10292,10293,10295],{},[2178,10294,2180],{},[2182,10296,1161],{},[2175,10298,10299,10301],{},[2178,10300,1640],{},[2178,10302,6578],{},[2172,10304,534],{"stretchy":6169},[3702,10306,10307,10309],{},[2172,10308,534],{"stretchy":6169},[2182,10310,1149],{},[2214,10312,10313],{"encoding":2216},"\\sum_{i=1}^{n} (y_i - (\\beta_0 + \\beta_1 x_i))^2",[83,10315,10317,10442,10500],{"className":10316,"ariaHidden":2204},[2221],[83,10318,10320,10323,10390,10393,10433,10436,10439],{"className":10319},[2225],[83,10321],{"className":10322,"style":9335},[2229],[83,10324,10326],{"className":10325},[9412,9413],[83,10327,10329,10382],{"className":10328},[2273,2274],[83,10330,10332,10379],{"className":10331},[2278],[83,10333,10335,10355,10365],{"className":10334,"style":9423},[2282],[83,10336,10337,10340],{"style":9426},[83,10338],{"className":10339,"style":9430},[2290],[83,10341,10343],{"className":10342},[2295,2296,2297,2298],[83,10344,10346,10349,10352],{"className":10345},[2234,2298],[83,10347,6578],{"className":10348},[2234,2264,2298],[83,10350,229],{"className":10351},[2247,2298],[83,10353,1161],{"className":10354},[2234,2298],[83,10356,10357,10360],{"style":9448},[83,10358],{"className":10359,"style":9430},[2290],[83,10361,10362],{},[83,10363,9260],{"className":10364},[9412,9457,9458],[83,10366,10367,10370],{"style":9461},[83,10368],{"className":10369,"style":9430},[2290],[83,10371,10373],{"className":10372},[2295,2296,2297,2298],[83,10374,10376],{"className":10375},[2234,2298],[83,10377,313],{"className":10378},[2234,2264,2298],[83,10380,2306],{"className":10381},[2305],[83,10383,10385],{"className":10384},[2278],[83,10386,10388],{"className":10387,"style":9483},[2282],[83,10389],{},[83,10391,187],{"className":10392},[6254],[83,10394,10396,10399],{"className":10395},[2234],[83,10397,3972],{"className":10398,"style":6311},[2234,2264],[83,10400,10402],{"className":10401},[2269],[83,10403,10405,10425],{"className":10404},[2273,2274],[83,10406,10408,10422],{"className":10407},[2278],[83,10409,10411],{"className":10410,"style":6610},[2282],[83,10412,10413,10416],{"style":6326},[83,10414],{"className":10415,"style":2291},[2290],[83,10417,10419],{"className":10418},[2295,2296,2297,2298],[83,10420,6578],{"className":10421},[2234,2264,2298],[83,10423,2306],{"className":10424},[2305],[83,10426,10428],{"className":10427},[2278],[83,10429,10431],{"className":10430,"style":2313},[2282],[83,10432],{},[83,10434],{"className":10435,"style":2319},[2242],[83,10437,8650],{"className":10438},[2323],[83,10440],{"className":10441,"style":2319},[2242],[83,10443,10445,10448,10451,10491,10494,10497],{"className":10444},[2225],[83,10446],{"className":10447,"style":6250},[2229],[83,10449,187],{"className":10450},[6254],[83,10452,10454,10457],{"className":10453},[2234],[83,10455,2180],{"className":10456,"style":2265},[2234,2264],[83,10458,10460],{"className":10459},[2269],[83,10461,10463,10483],{"className":10462},[2273,2274],[83,10464,10466,10480],{"className":10465},[2278],[83,10467,10469],{"className":10468,"style":2283},[2282],[83,10470,10471,10474],{"style":2286},[83,10472],{"className":10473,"style":2291},[2290],[83,10475,10477],{"className":10476},[2295,2296,2297,2298],[83,10478,411],{"className":10479},[2234,2298],[83,10481,2306],{"className":10482},[2305],[83,10484,10486],{"className":10485},[2278],[83,10487,10489],{"className":10488,"style":2313},[2282],[83,10490],{},[83,10492],{"className":10493,"style":2319},[2242],[83,10495,2186],{"className":10496},[2323],[83,10498],{"className":10499,"style":2319},[2242],[83,10501,10503,10506,10546,10586,10589],{"className":10502},[2225],[83,10504],{"className":10505,"style":9544},[2229],[83,10507,10509,10512],{"className":10508},[2234],[83,10510,2180],{"className":10511,"style":2265},[2234,2264],[83,10513,10515],{"className":10514},[2269],[83,10516,10518,10538],{"className":10517},[2273,2274],[83,10519,10521,10535],{"className":10520},[2278],[83,10522,10524],{"className":10523,"style":2283},[2282],[83,10525,10526,10529],{"style":2286},[83,10527],{"className":10528,"style":2291},[2290],[83,10530,10532],{"className":10531},[2295,2296,2297,2298],[83,10533,1161],{"className":10534},[2234,2298],[83,10536,2306],{"className":10537},[2305],[83,10539,10541],{"className":10540},[2278],[83,10542,10544],{"className":10543,"style":2313},[2282],[83,10545],{},[83,10547,10549,10552],{"className":10548},[2234],[83,10550,1640],{"className":10551},[2234,2264],[83,10553,10555],{"className":10554},[2269],[83,10556,10558,10578],{"className":10557},[2273,2274],[83,10559,10561,10575],{"className":10560},[2278],[83,10562,10564],{"className":10563,"style":6610},[2282],[83,10565,10566,10569],{"style":6276},[83,10567],{"className":10568,"style":2291},[2290],[83,10570,10572],{"className":10571},[2295,2296,2297,2298],[83,10573,6578],{"className":10574},[2234,2264,2298],[83,10576,2306],{"className":10577},[2305],[83,10579,10581],{"className":10580},[2278],[83,10582,10584],{"className":10583,"style":2313},[2282],[83,10585],{},[83,10587,534],{"className":10588},[6350],[83,10590,10592,10595],{"className":10591},[6350],[83,10593,534],{"className":10594},[6350],[83,10596,10598],{"className":10597},[2269],[83,10599,10601],{"className":10600},[2273],[83,10602,10604],{"className":10603},[2278],[83,10605,10607],{"className":10606,"style":9642},[2282],[83,10608,10609,10612],{"style":9645},[83,10610],{"className":10611,"style":2291},[2290],[83,10613,10615],{"className":10614},[2295,2296,2297,2298],[83,10616,1149],{"className":10617},[2234,2298],[12,10619,10620,10621,10624,10625,10659],{},"A esto se le conoce como el ",[40,10622,10623],{},"método de mínimos cuadrados",", y es una técnica comúnmente utilizada para encontrar los coeficientes ",[83,10626,10628,10641],{"className":10627},[2151],[83,10629,10631],{"className":10630},[2155],[2157,10632,10633],{"xmlns":2159},[2162,10634,10635,10639],{},[2165,10636,10637],{},[2178,10638,2180],{"mathvariant":8304},[2214,10640,8307],{"encoding":2216},[83,10642,10644],{"className":10643,"ariaHidden":2204},[2221],[83,10645,10647,10650],{"className":10646},[2225],[83,10648],{"className":10649,"style":2257},[2229],[83,10651,10653],{"className":10652},[2234],[83,10654,10656],{"className":10655},[2234],[83,10657,2180],{"className":10658,"style":8327},[2234,8326]," que mejor se ajusten a los datos.",[2073,10661,10662],{},[12,10663,10664],{},"¿Por qué se usan cuadrados? Porque al elevar al cuadrado las diferencias, se penalizan más los errores grandes, lo que ayuda a encontrar una mejor línea de ajuste para los datos.",[12,10666,10667,10668,10702,10703,1966,10772,10842],{},"Veamos ahora como obtenemos esos coeficientes ",[83,10669,10671,10684],{"className":10670},[2151],[83,10672,10674],{"className":10673},[2155],[2157,10675,10676],{"xmlns":2159},[2162,10677,10678,10682],{},[2165,10679,10680],{},[2178,10681,2180],{"mathvariant":8304},[2214,10683,8307],{"encoding":2216},[83,10685,10687],{"className":10686,"ariaHidden":2204},[2221],[83,10688,10690,10693],{"className":10689},[2225],[83,10691],{"className":10692,"style":2257},[2229],[83,10694,10696],{"className":10695},[2234],[83,10697,10699],{"className":10698},[2234],[83,10700,2180],{"className":10701,"style":8327},[2234,8326]," utilizando el método de mínimos cuadrados. Para encontrar los valores de ",[83,10704,10706,10723],{"className":10705},[2151],[83,10707,10709],{"className":10708},[2155],[2157,10710,10711],{"xmlns":2159},[2162,10712,10713,10721],{},[2165,10714,10715],{},[2175,10716,10717,10719],{},[2178,10718,2180],{},[2182,10720,411],{},[2214,10722,7853],{"encoding":2216},[83,10724,10726],{"className":10725,"ariaHidden":2204},[2221],[83,10727,10729,10732],{"className":10728},[2225],[83,10730],{"className":10731,"style":2257},[2229],[83,10733,10735,10738],{"className":10734},[2234],[83,10736,2180],{"className":10737,"style":2265},[2234,2264],[83,10739,10741],{"className":10740},[2269],[83,10742,10744,10764],{"className":10743},[2273,2274],[83,10745,10747,10761],{"className":10746},[2278],[83,10748,10750],{"className":10749,"style":2283},[2282],[83,10751,10752,10755],{"style":2286},[83,10753],{"className":10754,"style":2291},[2290],[83,10756,10758],{"className":10757},[2295,2296,2297,2298],[83,10759,411],{"className":10760},[2234,2298],[83,10762,2306],{"className":10763},[2305],[83,10765,10767],{"className":10766},[2278],[83,10768,10770],{"className":10769,"style":2313},[2282],[83,10771],{},[83,10773,10775,10793],{"className":10774},[2151],[83,10776,10778],{"className":10777},[2155],[2157,10779,10780],{"xmlns":2159},[2162,10781,10782,10790],{},[2165,10783,10784],{},[2175,10785,10786,10788],{},[2178,10787,2180],{},[2182,10789,1161],{},[2214,10791,10792],{"encoding":2216},"\\beta_1",[83,10794,10796],{"className":10795,"ariaHidden":2204},[2221],[83,10797,10799,10802],{"className":10798},[2225],[83,10800],{"className":10801,"style":2257},[2229],[83,10803,10805,10808],{"className":10804},[2234],[83,10806,2180],{"className":10807,"style":2265},[2234,2264],[83,10809,10811],{"className":10810},[2269],[83,10812,10814,10834],{"className":10813},[2273,2274],[83,10815,10817,10831],{"className":10816},[2278],[83,10818,10820],{"className":10819,"style":2283},[2282],[83,10821,10822,10825],{"style":2286},[83,10823],{"className":10824,"style":2291},[2290],[83,10826,10828],{"className":10827},[2295,2296,2297,2298],[83,10829,1161],{"className":10830},[2234,2298],[83,10832,2306],{"className":10833},[2305],[83,10835,10837],{"className":10836},[2278],[83,10838,10840],{"className":10839,"style":2313},[2282],[83,10841],{},", podemos usar las siguientes fórmulas, que se obtienen al derivar la función de pérdida MSE con respecto a los coeficientes y establecer las derivadas iguales a cero:",[83,10844,10846],{"className":10845},[2147],[83,10847,10849,10948],{"className":10848},[2151],[83,10850,10852],{"className":10851},[2155],[2157,10853,10854],{"xmlns":2159,"display":2160},[2162,10855,10856,10945],{},[2165,10857,10858,10864,10866],{},[2175,10859,10860,10862],{},[2178,10861,2180],{},[2182,10863,1161],{},[2172,10865,229],{},[9249,10867,10868,10908],{},[2165,10869,10870,10872,10874,10876,10882,10888,10890,10892,10894,10900,10902],{},[2178,10871,313],{},[2172,10873,9260],{},[2172,10875,187],{"stretchy":6169},[2175,10877,10878,10880],{},[2178,10879,1640],{},[2178,10881,6578],{},[2175,10883,10884,10886],{},[2178,10885,3972],{},[2178,10887,6578],{},[2172,10889,534],{"stretchy":6169},[2172,10891,8650],{},[2172,10893,9260],{},[2175,10895,10896,10898],{},[2178,10897,1640],{},[2178,10899,6578],{},[2172,10901,9260],{},[2175,10903,10904,10906],{},[2178,10905,3972],{},[2178,10907,6578],{},[2165,10909,10910,10912,10914,10916,10925,10927,10929,10931,10933,10939],{},[2178,10911,313],{},[2172,10913,9260],{},[2172,10915,187],{"stretchy":6169},[10917,10918,10919,10921,10923],"msubsup",{},[2178,10920,1640],{},[2178,10922,6578],{},[2182,10924,1149],{},[2172,10926,534],{"stretchy":6169},[2172,10928,8650],{},[2172,10930,187],{"stretchy":6169},[2172,10932,9260],{},[2175,10934,10935,10937],{},[2178,10936,1640],{},[2178,10938,6578],{},[3702,10940,10941,10943],{},[2172,10942,534],{"stretchy":6169},[2182,10944,1149],{},[2214,10946,10947],{"encoding":2216},"\\beta_1 = \\frac{n \\sum (x_i y_i) - \\sum x_i \\sum y_i}{n \\sum (x_i^2) - (\\sum x_i)^2}",[83,10949,10951,11006],{"className":10950,"ariaHidden":2204},[2221],[83,10952,10954,10957,10997,11000,11003],{"className":10953},[2225],[83,10955],{"className":10956,"style":2257},[2229],[83,10958,10960,10963],{"className":10959},[2234],[83,10961,2180],{"className":10962,"style":2265},[2234,2264],[83,10964,10966],{"className":10965},[2269],[83,10967,10969,10989],{"className":10968},[2273,2274],[83,10970,10972,10986],{"className":10971},[2278],[83,10973,10975],{"className":10974,"style":2283},[2282],[83,10976,10977,10980],{"style":2286},[83,10978],{"className":10979,"style":2291},[2290],[83,10981,10983],{"className":10982},[2295,2296,2297,2298],[83,10984,1161],{"className":10985},[2234,2298],[83,10987,2306],{"className":10988},[2305],[83,10990,10992],{"className":10991},[2278],[83,10993,10995],{"className":10994,"style":2313},[2282],[83,10996],{},[83,10998],{"className":10999,"style":2243},[2242],[83,11001,229],{"className":11002},[2247],[83,11004],{"className":11005,"style":2243},[2242],[83,11007,11009,11013],{"className":11008},[2225],[83,11010],{"className":11011,"style":11012},[2229],"height:2.3899em;vertical-align:-0.9629em;",[83,11014,11016,11019,11428],{"className":11015},[2234],[83,11017],{"className":11018},[6254,9342],[83,11020,11022],{"className":11021},[9249],[83,11023,11025,11419],{"className":11024},[2273,2274],[83,11026,11028,11416],{"className":11027},[2278],[83,11029,11032,11201,11209],{"className":11030,"style":11031},[2282],"height:1.427em;",[83,11033,11034,11037],{"style":9358},[83,11035],{"className":11036,"style":2414},[2290],[83,11038,11040,11043,11046,11051,11054,11109,11112,11115,11118,11121,11124,11127,11130,11170],{"className":11039},[2234],[83,11041,313],{"className":11042},[2234,2264],[83,11044],{"className":11045,"style":6304},[2242],[83,11047,9260],{"className":11048,"style":11050},[9412,9457,11049],"small-op","position:relative;top:0em;",[83,11052,187],{"className":11053},[6254],[83,11055,11057,11060],{"className":11056},[2234],[83,11058,1640],{"className":11059},[2234,2264],[83,11061,11063],{"className":11062},[2269],[83,11064,11066,11100],{"className":11065},[2273,2274],[83,11067,11069,11097],{"className":11068},[2278],[83,11070,11073,11085],{"className":11071,"style":11072},[2282],"height:0.7959em;",[83,11074,11076,11079],{"style":11075},"top:-2.4231em;margin-left:0em;margin-right:0.05em;",[83,11077],{"className":11078,"style":2291},[2290],[83,11080,11082],{"className":11081},[2295,2296,2297,2298],[83,11083,6578],{"className":11084},[2234,2264,2298],[83,11086,11088,11091],{"style":11087},"top:-3.0448em;margin-right:0.05em;",[83,11089],{"className":11090,"style":2291},[2290],[83,11092,11094],{"className":11093},[2295,2296,2297,2298],[83,11095,1149],{"className":11096},[2234,2298],[83,11098,2306],{"className":11099},[2305],[83,11101,11103],{"className":11102},[2278],[83,11104,11107],{"className":11105,"style":11106},[2282],"height:0.2769em;",[83,11108],{},[83,11110,534],{"className":11111},[6350],[83,11113],{"className":11114,"style":2319},[2242],[83,11116,8650],{"className":11117},[2323],[83,11119],{"className":11120,"style":2319},[2242],[83,11122,187],{"className":11123},[6254],[83,11125,9260],{"className":11126,"style":11050},[9412,9457,11049],[83,11128],{"className":11129,"style":6304},[2242],[83,11131,11133,11136],{"className":11132},[2234],[83,11134,1640],{"className":11135},[2234,2264],[83,11137,11139],{"className":11138},[2269],[83,11140,11142,11162],{"className":11141},[2273,2274],[83,11143,11145,11159],{"className":11144},[2278],[83,11146,11148],{"className":11147,"style":6610},[2282],[83,11149,11150,11153],{"style":6276},[83,11151],{"className":11152,"style":2291},[2290],[83,11154,11156],{"className":11155},[2295,2296,2297,2298],[83,11157,6578],{"className":11158},[2234,2264,2298],[83,11160,2306],{"className":11161},[2305],[83,11163,11165],{"className":11164},[2278],[83,11166,11168],{"className":11167,"style":2313},[2282],[83,11169],{},[83,11171,11173,11176],{"className":11172},[6350],[83,11174,534],{"className":11175},[6350],[83,11177,11179],{"className":11178},[2269],[83,11180,11182],{"className":11181},[2273],[83,11183,11185],{"className":11184},[2278],[83,11186,11189],{"className":11187,"style":11188},[2282],"height:0.7401em;",[83,11190,11192,11195],{"style":11191},"top:-2.989em;margin-right:0.05em;",[83,11193],{"className":11194,"style":2291},[2290],[83,11196,11198],{"className":11197},[2295,2296,2297,2298],[83,11199,1149],{"className":11200},[2234,2298],[83,11202,11203,11206],{"style":9370},[83,11204],{"className":11205,"style":2414},[2290],[83,11207],{"className":11208,"style":9378},[9377],[83,11210,11211,11214],{"style":9381},[83,11212],{"className":11213,"style":2414},[2290],[83,11215,11217,11220,11223,11226,11229,11269,11309,11312,11315,11318,11321,11324,11327,11367,11370,11373,11376],{"className":11216},[2234],[83,11218,313],{"className":11219},[2234,2264],[83,11221],{"className":11222,"style":6304},[2242],[83,11224,9260],{"className":11225,"style":11050},[9412,9457,11049],[83,11227,187],{"className":11228},[6254],[83,11230,11232,11235],{"className":11231},[2234],[83,11233,1640],{"className":11234},[2234,2264],[83,11236,11238],{"className":11237},[2269],[83,11239,11241,11261],{"className":11240},[2273,2274],[83,11242,11244,11258],{"className":11243},[2278],[83,11245,11247],{"className":11246,"style":6610},[2282],[83,11248,11249,11252],{"style":6276},[83,11250],{"className":11251,"style":2291},[2290],[83,11253,11255],{"className":11254},[2295,2296,2297,2298],[83,11256,6578],{"className":11257},[2234,2264,2298],[83,11259,2306],{"className":11260},[2305],[83,11262,11264],{"className":11263},[2278],[83,11265,11267],{"className":11266,"style":2313},[2282],[83,11268],{},[83,11270,11272,11275],{"className":11271},[2234],[83,11273,3972],{"className":11274,"style":6311},[2234,2264],[83,11276,11278],{"className":11277},[2269],[83,11279,11281,11301],{"className":11280},[2273,2274],[83,11282,11284,11298],{"className":11283},[2278],[83,11285,11287],{"className":11286,"style":6610},[2282],[83,11288,11289,11292],{"style":6326},[83,11290],{"className":11291,"style":2291},[2290],[83,11293,11295],{"className":11294},[2295,2296,2297,2298],[83,11296,6578],{"className":11297},[2234,2264,2298],[83,11299,2306],{"className":11300},[2305],[83,11302,11304],{"className":11303},[2278],[83,11305,11307],{"className":11306,"style":2313},[2282],[83,11308],{},[83,11310,534],{"className":11311},[6350],[83,11313],{"className":11314,"style":2319},[2242],[83,11316,8650],{"className":11317},[2323],[83,11319],{"className":11320,"style":2319},[2242],[83,11322,9260],{"className":11323,"style":11050},[9412,9457,11049],[83,11325],{"className":11326,"style":6304},[2242],[83,11328,11330,11333],{"className":11329},[2234],[83,11331,1640],{"className":11332},[2234,2264],[83,11334,11336],{"className":11335},[2269],[83,11337,11339,11359],{"className":11338},[2273,2274],[83,11340,11342,11356],{"className":11341},[2278],[83,11343,11345],{"className":11344,"style":6610},[2282],[83,11346,11347,11350],{"style":6276},[83,11348],{"className":11349,"style":2291},[2290],[83,11351,11353],{"className":11352},[2295,2296,2297,2298],[83,11354,6578],{"className":11355},[2234,2264,2298],[83,11357,2306],{"className":11358},[2305],[83,11360,11362],{"className":11361},[2278],[83,11363,11365],{"className":11364,"style":2313},[2282],[83,11366],{},[83,11368],{"className":11369,"style":6304},[2242],[83,11371,9260],{"className":11372,"style":11050},[9412,9457,11049],[83,11374],{"className":11375,"style":6304},[2242],[83,11377,11379,11382],{"className":11378},[2234],[83,11380,3972],{"className":11381,"style":6311},[2234,2264],[83,11383,11385],{"className":11384},[2269],[83,11386,11388,11408],{"className":11387},[2273,2274],[83,11389,11391,11405],{"className":11390},[2278],[83,11392,11394],{"className":11393,"style":6610},[2282],[83,11395,11396,11399],{"style":6326},[83,11397],{"className":11398,"style":2291},[2290],[83,11400,11402],{"className":11401},[2295,2296,2297,2298],[83,11403,6578],{"className":11404},[2234,2264,2298],[83,11406,2306],{"className":11407},[2305],[83,11409,11411],{"className":11410},[2278],[83,11412,11414],{"className":11413,"style":2313},[2282],[83,11415],{},[83,11417,2306],{"className":11418},[2305],[83,11420,11422],{"className":11421},[2278],[83,11423,11426],{"className":11424,"style":11425},[2282],"height:0.9629em;",[83,11427],{},[83,11429],{"className":11430},[6350,9342],[83,11432,11434],{"className":11433},[2147],[83,11435,11437,11478],{"className":11436},[2151],[83,11438,11440],{"className":11439},[2155],[2157,11441,11442],{"xmlns":2159,"display":2160},[2162,11443,11444,11475],{},[2165,11445,11446,11452,11454,11461,11463,11469],{},[2175,11447,11448,11450],{},[2178,11449,2180],{},[2182,11451,411],{},[2172,11453,229],{},[2202,11455,11456,11458],{"accent":2204},[2178,11457,3972],{},[2172,11459,11460],{},"ˉ",[2172,11462,8650],{},[2175,11464,11465,11467],{},[2178,11466,2180],{},[2182,11468,1161],{},[2202,11470,11471,11473],{"accent":2204},[2178,11472,1640],{},[2172,11474,11460],{},[2214,11476,11477],{"encoding":2216},"\\beta_0 = \\bar{y} - \\beta_1 \\bar{x}",[83,11479,11481,11536,11594],{"className":11480,"ariaHidden":2204},[2221],[83,11482,11484,11487,11527,11530,11533],{"className":11483},[2225],[83,11485],{"className":11486,"style":2257},[2229],[83,11488,11490,11493],{"className":11489},[2234],[83,11491,2180],{"className":11492,"style":2265},[2234,2264],[83,11494,11496],{"className":11495},[2269],[83,11497,11499,11519],{"className":11498},[2273,2274],[83,11500,11502,11516],{"className":11501},[2278],[83,11503,11505],{"className":11504,"style":2283},[2282],[83,11506,11507,11510],{"style":2286},[83,11508],{"className":11509,"style":2291},[2290],[83,11511,11513],{"className":11512},[2295,2296,2297,2298],[83,11514,411],{"className":11515},[2234,2298],[83,11517,2306],{"className":11518},[2305],[83,11520,11522],{"className":11521},[2278],[83,11523,11525],{"className":11524,"style":2313},[2282],[83,11526],{},[83,11528],{"className":11529,"style":2243},[2242],[83,11531,229],{"className":11532},[2247],[83,11534],{"className":11535,"style":2243},[2242],[83,11537,11539,11542,11585,11588,11591],{"className":11538},[2225],[83,11540],{"className":11541,"style":8737},[2229],[83,11543,11545],{"className":11544},[2234,2398],[83,11546,11548,11577],{"className":11547},[2273,2274],[83,11549,11551,11574],{"className":11550},[2278],[83,11552,11555,11563],{"className":11553,"style":11554},[2282],"height:0.5678em;",[83,11556,11557,11560],{"style":2410},[83,11558],{"className":11559,"style":2414},[2290],[83,11561,3972],{"className":11562,"style":6311},[2234,2264],[83,11564,11565,11568],{"style":2410},[83,11566],{"className":11567,"style":2414},[2290],[83,11569,11571],{"className":11570,"style":9858},[2426],[83,11572,11460],{"className":11573},[2234],[83,11575,2306],{"className":11576},[2305],[83,11578,11580],{"className":11579},[2278],[83,11581,11583],{"className":11582,"style":8875},[2282],[83,11584],{},[83,11586],{"className":11587,"style":2319},[2242],[83,11589,8650],{"className":11590},[2323],[83,11592],{"className":11593,"style":2319},[2242],[83,11595,11597,11600,11640],{"className":11596},[2225],[83,11598],{"className":11599,"style":2257},[2229],[83,11601,11603,11606],{"className":11602},[2234],[83,11604,2180],{"className":11605,"style":2265},[2234,2264],[83,11607,11609],{"className":11608},[2269],[83,11610,11612,11632],{"className":11611},[2273,2274],[83,11613,11615,11629],{"className":11614},[2278],[83,11616,11618],{"className":11617,"style":2283},[2282],[83,11619,11620,11623],{"style":2286},[83,11621],{"className":11622,"style":2291},[2290],[83,11624,11626],{"className":11625},[2295,2296,2297,2298],[83,11627,1161],{"className":11628},[2234,2298],[83,11630,2306],{"className":11631},[2305],[83,11633,11635],{"className":11634},[2278],[83,11636,11638],{"className":11637,"style":2313},[2282],[83,11639],{},[83,11641,11643],{"className":11642},[2234,2398],[83,11644,11646],{"className":11645},[2273],[83,11647,11649],{"className":11648},[2278],[83,11650,11652,11660],{"className":11651,"style":11554},[2282],[83,11653,11654,11657],{"style":2410},[83,11655],{"className":11656,"style":2414},[2290],[83,11658,1640],{"className":11659},[2234,2264],[83,11661,11662,11665],{"style":2410},[83,11663],{"className":11664,"style":2414},[2290],[83,11666,11669],{"className":11667,"style":11668},[2426],"left:-0.2222em;",[83,11670,11460],{"className":11671},[2234],[12,11673,7598],{},[1359,11675,11676,11706,11847],{},[1362,11677,11678,9689],{},[83,11679,11681,11694],{"className":11680},[2151],[83,11682,11684],{"className":11683},[2155],[2157,11685,11686],{"xmlns":2159},[2162,11687,11688,11692],{},[2165,11689,11690],{},[2178,11691,313],{},[2214,11693,313],{"encoding":2216},[83,11695,11697],{"className":11696,"ariaHidden":2204},[2221],[83,11698,11700,11703],{"className":11699},[2225],[83,11701],{"className":11702,"style":7592},[2229],[83,11704,313],{"className":11705},[2234,2264],[1362,11707,11708,1966,11777,11846],{},[83,11709,11711,11728],{"className":11710},[2151],[83,11712,11714],{"className":11713},[2155],[2157,11715,11716],{"xmlns":2159},[2162,11717,11718,11726],{},[2165,11719,11720],{},[2175,11721,11722,11724],{},[2178,11723,1640],{},[2178,11725,6578],{},[2214,11727,6581],{"encoding":2216},[83,11729,11731],{"className":11730,"ariaHidden":2204},[2221],[83,11732,11734,11737],{"className":11733},[2225],[83,11735],{"className":11736,"style":6591},[2229],[83,11738,11740,11743],{"className":11739},[2234],[83,11741,1640],{"className":11742},[2234,2264],[83,11744,11746],{"className":11745},[2269],[83,11747,11749,11769],{"className":11748},[2273,2274],[83,11750,11752,11766],{"className":11751},[2278],[83,11753,11755],{"className":11754,"style":6610},[2282],[83,11756,11757,11760],{"style":6276},[83,11758],{"className":11759,"style":2291},[2290],[83,11761,11763],{"className":11762},[2295,2296,2297,2298],[83,11764,6578],{"className":11765},[2234,2264,2298],[83,11767,2306],{"className":11768},[2305],[83,11770,11772],{"className":11771},[2278],[83,11773,11775],{"className":11774,"style":2313},[2282],[83,11776],{},[83,11778,11780,11797],{"className":11779},[2151],[83,11781,11783],{"className":11782},[2155],[2157,11784,11785],{"xmlns":2159},[2162,11786,11787,11795],{},[2165,11788,11789],{},[2175,11790,11791,11793],{},[2178,11792,3972],{},[2178,11794,6578],{},[2214,11796,6654],{"encoding":2216},[83,11798,11800],{"className":11799,"ariaHidden":2204},[2221],[83,11801,11803,11806],{"className":11802},[2225],[83,11804],{"className":11805,"style":6664},[2229],[83,11807,11809,11812],{"className":11808},[2234],[83,11810,3972],{"className":11811,"style":6311},[2234,2264],[83,11813,11815],{"className":11814},[2269],[83,11816,11818,11838],{"className":11817},[2273,2274],[83,11819,11821,11835],{"className":11820},[2278],[83,11822,11824],{"className":11823,"style":6610},[2282],[83,11825,11826,11829],{"style":6326},[83,11827],{"className":11828,"style":2291},[2290],[83,11830,11832],{"className":11831},[2295,2296,2297,2298],[83,11833,6578],{"className":11834},[2234,2264,2298],[83,11836,2306],{"className":11837},[2305],[83,11839,11841],{"className":11840},[2278],[83,11842,11844],{"className":11843,"style":2313},[2282],[83,11845],{}," son los valores de las variables independientes y dependientes para cada ejemplo.",[1362,11848,11849,1966,11910,11983],{},[83,11850,11852,11870],{"className":11851},[2151],[83,11853,11855],{"className":11854},[2155],[2157,11856,11857],{"xmlns":2159},[2162,11858,11859,11867],{},[2165,11860,11861],{},[2202,11862,11863,11865],{"accent":2204},[2178,11864,1640],{},[2172,11866,11460],{},[2214,11868,11869],{"encoding":2216},"\\bar{x}",[83,11871,11873],{"className":11872,"ariaHidden":2204},[2221],[83,11874,11876,11879],{"className":11875},[2225],[83,11877],{"className":11878,"style":11554},[2229],[83,11880,11882],{"className":11881},[2234,2398],[83,11883,11885],{"className":11884},[2273],[83,11886,11888],{"className":11887},[2278],[83,11889,11891,11899],{"className":11890,"style":11554},[2282],[83,11892,11893,11896],{"style":2410},[83,11894],{"className":11895,"style":2414},[2290],[83,11897,1640],{"className":11898},[2234,2264],[83,11900,11901,11904],{"style":2410},[83,11902],{"className":11903,"style":2414},[2290],[83,11905,11907],{"className":11906,"style":11668},[2426],[83,11908,11460],{"className":11909},[2234],[83,11911,11913,11931],{"className":11912},[2151],[83,11914,11916],{"className":11915},[2155],[2157,11917,11918],{"xmlns":2159},[2162,11919,11920,11928],{},[2165,11921,11922],{},[2202,11923,11924,11926],{"accent":2204},[2178,11925,3972],{},[2172,11927,11460],{},[2214,11929,11930],{"encoding":2216},"\\bar{y}",[83,11932,11934],{"className":11933,"ariaHidden":2204},[2221],[83,11935,11937,11941],{"className":11936},[2225],[83,11938],{"className":11939,"style":11940},[2229],"height:0.7622em;vertical-align:-0.1944em;",[83,11942,11944],{"className":11943},[2234,2398],[83,11945,11947,11975],{"className":11946},[2273,2274],[83,11948,11950,11972],{"className":11949},[2278],[83,11951,11953,11961],{"className":11952,"style":11554},[2282],[83,11954,11955,11958],{"style":2410},[83,11956],{"className":11957,"style":2414},[2290],[83,11959,3972],{"className":11960,"style":6311},[2234,2264],[83,11962,11963,11966],{"style":2410},[83,11964],{"className":11965,"style":2414},[2290],[83,11967,11969],{"className":11968,"style":9858},[2426],[83,11970,11460],{"className":11971},[2234],[83,11973,2306],{"className":11974},[2305],[83,11976,11978],{"className":11977},[2278],[83,11979,11981],{"className":11980,"style":8875},[2282],[83,11982],{}," son las medias (o promedios) de las variables independientes y dependientes, respectivamente.",[12,11985,11986],{},"Hagámos un ejemplo para entender como aplicarlo. Supongamos que tenemos un conjunto de datos con las siguientes características:",[3070,11988,11989,11999],{},[3073,11990,11991],{},[3076,11992,11993,11996],{},[3079,11994,11995],{},"Tamaño (m²)",[3079,11997,11998],{},"Precio (USD)",[3086,12000,12001,12009,12017],{},[3076,12002,12003,12006],{},[3091,12004,12005],{},"50",[3091,12007,12008],{},"100,000",[3076,12010,12011,12014],{},[3091,12012,12013],{},"100",[3091,12015,12016],{},"200,000",[3076,12018,12019,12022],{},[3091,12020,12021],{},"150",[3091,12023,12024],{},"300,000",[12,12026,12027,12028,12031],{},"Queremos construir un modelo de regresión lineal para ",[40,12029,12030],{},"predecir el precio"," de una casa basándonos en su tamaño. En este caso, la variable independiente es el tamaño (X) y la variable dependiente es el precio (Y). El modelo de regresión lineal se puede expresar como:",[83,12033,12035],{"className":12034},[2147],[83,12036,12038,12074],{"className":12037},[2151],[83,12039,12041],{"className":12040},[2155],[2157,12042,12043],{"xmlns":2159,"display":2160},[2162,12044,12045,12071],{},[2165,12046,12047,12049,12051,12057,12059,12065,12067,12069],{},[2178,12048,3972],{},[2172,12050,229],{},[2175,12052,12053,12055],{},[2178,12054,2180],{},[2182,12056,411],{},[2172,12058,2186],{},[2175,12060,12061,12063],{},[2178,12062,2180],{},[2182,12064,1161],{},[2178,12066,1640],{},[2172,12068,2186],{},[2178,12070,7200],{},[2214,12072,12073],{"encoding":2216},"y = \\beta_0 + \\beta_1 x + \\epsilon",[83,12075,12077,12095,12150,12208],{"className":12076,"ariaHidden":2204},[2221],[83,12078,12080,12083,12086,12089,12092],{"className":12079},[2225],[83,12081],{"className":12082,"style":6664},[2229],[83,12084,3972],{"className":12085,"style":6311},[2234,2264],[83,12087],{"className":12088,"style":2243},[2242],[83,12090,229],{"className":12091},[2247],[83,12093],{"className":12094,"style":2243},[2242],[83,12096,12098,12101,12141,12144,12147],{"className":12097},[2225],[83,12099],{"className":12100,"style":2257},[2229],[83,12102,12104,12107],{"className":12103},[2234],[83,12105,2180],{"className":12106,"style":2265},[2234,2264],[83,12108,12110],{"className":12109},[2269],[83,12111,12113,12133],{"className":12112},[2273,2274],[83,12114,12116,12130],{"className":12115},[2278],[83,12117,12119],{"className":12118,"style":2283},[2282],[83,12120,12121,12124],{"style":2286},[83,12122],{"className":12123,"style":2291},[2290],[83,12125,12127],{"className":12126},[2295,2296,2297,2298],[83,12128,411],{"className":12129},[2234,2298],[83,12131,2306],{"className":12132},[2305],[83,12134,12136],{"className":12135},[2278],[83,12137,12139],{"className":12138,"style":2313},[2282],[83,12140],{},[83,12142],{"className":12143,"style":2319},[2242],[83,12145,2186],{"className":12146},[2323],[83,12148],{"className":12149,"style":2319},[2242],[83,12151,12153,12156,12196,12199,12202,12205],{"className":12152},[2225],[83,12154],{"className":12155,"style":2257},[2229],[83,12157,12159,12162],{"className":12158},[2234],[83,12160,2180],{"className":12161,"style":2265},[2234,2264],[83,12163,12165],{"className":12164},[2269],[83,12166,12168,12188],{"className":12167},[2273,2274],[83,12169,12171,12185],{"className":12170},[2278],[83,12172,12174],{"className":12173,"style":2283},[2282],[83,12175,12176,12179],{"style":2286},[83,12177],{"className":12178,"style":2291},[2290],[83,12180,12182],{"className":12181},[2295,2296,2297,2298],[83,12183,1161],{"className":12184},[2234,2298],[83,12186,2306],{"className":12187},[2305],[83,12189,12191],{"className":12190},[2278],[83,12192,12194],{"className":12193,"style":2313},[2282],[83,12195],{},[83,12197,1640],{"className":12198},[2234,2264],[83,12200],{"className":12201,"style":2319},[2242],[83,12203,2186],{"className":12204},[2323],[83,12206],{"className":12207,"style":2319},[2242],[83,12209,12211,12214],{"className":12210},[2225],[83,12212],{"className":12213,"style":7592},[2229],[83,12215,7200],{"className":12216},[2234,2264],[12,12218,7598],{},[1359,12220,12221,12252,12283,12355,12427],{},[1362,12222,12223,12251],{},[83,12224,12226,12239],{"className":12225},[2151],[83,12227,12229],{"className":12228},[2155],[2157,12230,12231],{"xmlns":2159},[2162,12232,12233,12237],{},[2165,12234,12235],{},[2178,12236,3972],{},[2214,12238,3972],{"encoding":2216},[83,12240,12242],{"className":12241,"ariaHidden":2204},[2221],[83,12243,12245,12248],{"className":12244},[2225],[83,12246],{"className":12247,"style":6664},[2229],[83,12249,3972],{"className":12250,"style":6311},[2234,2264]," es el precio de la casa.",[1362,12253,12254,12282],{},[83,12255,12257,12270],{"className":12256},[2151],[83,12258,12260],{"className":12259},[2155],[2157,12261,12262],{"xmlns":2159},[2162,12263,12264,12268],{},[2165,12265,12266],{},[2178,12267,1640],{},[2214,12269,1640],{"encoding":2216},[83,12271,12273],{"className":12272,"ariaHidden":2204},[2221],[83,12274,12276,12279],{"className":12275},[2225],[83,12277],{"className":12278,"style":7592},[2229],[83,12280,1640],{"className":12281},[2234,2264]," es el tamaño de la casa.",[1362,12284,12285,12354],{},[83,12286,12288,12305],{"className":12287},[2151],[83,12289,12291],{"className":12290},[2155],[2157,12292,12293],{"xmlns":2159},[2162,12294,12295,12303],{},[2165,12296,12297],{},[2175,12298,12299,12301],{},[2178,12300,2180],{},[2182,12302,411],{},[2214,12304,7853],{"encoding":2216},[83,12306,12308],{"className":12307,"ariaHidden":2204},[2221],[83,12309,12311,12314],{"className":12310},[2225],[83,12312],{"className":12313,"style":2257},[2229],[83,12315,12317,12320],{"className":12316},[2234],[83,12318,2180],{"className":12319,"style":2265},[2234,2264],[83,12321,12323],{"className":12322},[2269],[83,12324,12326,12346],{"className":12325},[2273,2274],[83,12327,12329,12343],{"className":12328},[2278],[83,12330,12332],{"className":12331,"style":2283},[2282],[83,12333,12334,12337],{"style":2286},[83,12335],{"className":12336,"style":2291},[2290],[83,12338,12340],{"className":12339},[2295,2296,2297,2298],[83,12341,411],{"className":12342},[2234,2298],[83,12344,2306],{"className":12345},[2305],[83,12347,12349],{"className":12348},[2278],[83,12350,12352],{"className":12351,"style":2313},[2282],[83,12353],{}," es el intercepto.",[1362,12356,12357,12426],{},[83,12358,12360,12377],{"className":12359},[2151],[83,12361,12363],{"className":12362},[2155],[2157,12364,12365],{"xmlns":2159},[2162,12366,12367,12375],{},[2165,12368,12369],{},[2175,12370,12371,12373],{},[2178,12372,2180],{},[2182,12374,1161],{},[2214,12376,10792],{"encoding":2216},[83,12378,12380],{"className":12379,"ariaHidden":2204},[2221],[83,12381,12383,12386],{"className":12382},[2225],[83,12384],{"className":12385,"style":2257},[2229],[83,12387,12389,12392],{"className":12388},[2234],[83,12390,2180],{"className":12391,"style":2265},[2234,2264],[83,12393,12395],{"className":12394},[2269],[83,12396,12398,12418],{"className":12397},[2273,2274],[83,12399,12401,12415],{"className":12400},[2278],[83,12402,12404],{"className":12403,"style":2283},[2282],[83,12405,12406,12409],{"style":2286},[83,12407],{"className":12408,"style":2291},[2290],[83,12410,12412],{"className":12411},[2295,2296,2297,2298],[83,12413,1161],{"className":12414},[2234,2298],[83,12416,2306],{"className":12417},[2305],[83,12419,12421],{"className":12420},[2278],[83,12422,12424],{"className":12423,"style":2313},[2282],[83,12425],{}," es la pendiente.",[1362,12428,12429,12457],{},[83,12430,12432,12445],{"className":12431},[2151],[83,12433,12435],{"className":12434},[2155],[2157,12436,12437],{"xmlns":2159},[2162,12438,12439,12443],{},[2165,12440,12441],{},[2178,12442,7200],{},[2214,12444,8178],{"encoding":2216},[83,12446,12448],{"className":12447,"ariaHidden":2204},[2221],[83,12449,12451,12454],{"className":12450},[2225],[83,12452],{"className":12453,"style":7592},[2229],[83,12455,7200],{"className":12456},[2234,2264]," es el error o ruido, que para este ejemplo asumiremos que es cero para simplificar.",[12,12459,12460,12461,1966,12530,12599],{},"Para encontrar los valores de ",[83,12462,12464,12481],{"className":12463},[2151],[83,12465,12467],{"className":12466},[2155],[2157,12468,12469],{"xmlns":2159},[2162,12470,12471,12479],{},[2165,12472,12473],{},[2175,12474,12475,12477],{},[2178,12476,2180],{},[2182,12478,411],{},[2214,12480,7853],{"encoding":2216},[83,12482,12484],{"className":12483,"ariaHidden":2204},[2221],[83,12485,12487,12490],{"className":12486},[2225],[83,12488],{"className":12489,"style":2257},[2229],[83,12491,12493,12496],{"className":12492},[2234],[83,12494,2180],{"className":12495,"style":2265},[2234,2264],[83,12497,12499],{"className":12498},[2269],[83,12500,12502,12522],{"className":12501},[2273,2274],[83,12503,12505,12519],{"className":12504},[2278],[83,12506,12508],{"className":12507,"style":2283},[2282],[83,12509,12510,12513],{"style":2286},[83,12511],{"className":12512,"style":2291},[2290],[83,12514,12516],{"className":12515},[2295,2296,2297,2298],[83,12517,411],{"className":12518},[2234,2298],[83,12520,2306],{"className":12521},[2305],[83,12523,12525],{"className":12524},[2278],[83,12526,12528],{"className":12527,"style":2313},[2282],[83,12529],{},[83,12531,12533,12550],{"className":12532},[2151],[83,12534,12536],{"className":12535},[2155],[2157,12537,12538],{"xmlns":2159},[2162,12539,12540,12548],{},[2165,12541,12542],{},[2175,12543,12544,12546],{},[2178,12545,2180],{},[2182,12547,1161],{},[2214,12549,10792],{"encoding":2216},[83,12551,12553],{"className":12552,"ariaHidden":2204},[2221],[83,12554,12556,12559],{"className":12555},[2225],[83,12557],{"className":12558,"style":2257},[2229],[83,12560,12562,12565],{"className":12561},[2234],[83,12563,2180],{"className":12564,"style":2265},[2234,2264],[83,12566,12568],{"className":12567},[2269],[83,12569,12571,12591],{"className":12570},[2273,2274],[83,12572,12574,12588],{"className":12573},[2278],[83,12575,12577],{"className":12576,"style":2283},[2282],[83,12578,12579,12582],{"style":2286},[83,12580],{"className":12581,"style":2291},[2290],[83,12583,12585],{"className":12584},[2295,2296,2297,2298],[83,12586,1161],{"className":12587},[2234,2298],[83,12589,2306],{"className":12590},[2305],[83,12592,12594],{"className":12593},[2278],[83,12595,12597],{"className":12596,"style":2313},[2282],[83,12598],{},", podemos usar el método de mínimos cuadrados con la fórmula que mencionamos anteriormente:",[83,12601,12603],{"className":12602},[2147],[83,12604,12606,12703],{"className":12605},[2151],[83,12607,12609],{"className":12608},[2155],[2157,12610,12611],{"xmlns":2159,"display":2160},[2162,12612,12613,12701],{},[2165,12614,12615,12621,12623],{},[2175,12616,12617,12619],{},[2178,12618,2180],{},[2182,12620,1161],{},[2172,12622,229],{},[9249,12624,12625,12665],{},[2165,12626,12627,12629,12631,12633,12639,12645,12647,12649,12651,12657,12659],{},[2178,12628,313],{},[2172,12630,9260],{},[2172,12632,187],{"stretchy":6169},[2175,12634,12635,12637],{},[2178,12636,1640],{},[2178,12638,6578],{},[2175,12640,12641,12643],{},[2178,12642,3972],{},[2178,12644,6578],{},[2172,12646,534],{"stretchy":6169},[2172,12648,8650],{},[2172,12650,9260],{},[2175,12652,12653,12655],{},[2178,12654,1640],{},[2178,12656,6578],{},[2172,12658,9260],{},[2175,12660,12661,12663],{},[2178,12662,3972],{},[2178,12664,6578],{},[2165,12666,12667,12669,12671,12673,12681,12683,12685,12687,12689,12695],{},[2178,12668,313],{},[2172,12670,9260],{},[2172,12672,187],{"stretchy":6169},[10917,12674,12675,12677,12679],{},[2178,12676,1640],{},[2178,12678,6578],{},[2182,12680,1149],{},[2172,12682,534],{"stretchy":6169},[2172,12684,8650],{},[2172,12686,187],{"stretchy":6169},[2172,12688,9260],{},[2175,12690,12691,12693],{},[2178,12692,1640],{},[2178,12694,6578],{},[3702,12696,12697,12699],{},[2172,12698,534],{"stretchy":6169},[2182,12700,1149],{},[2214,12702,10947],{"encoding":2216},[83,12704,12706,12761],{"className":12705,"ariaHidden":2204},[2221],[83,12707,12709,12712,12752,12755,12758],{"className":12708},[2225],[83,12710],{"className":12711,"style":2257},[2229],[83,12713,12715,12718],{"className":12714},[2234],[83,12716,2180],{"className":12717,"style":2265},[2234,2264],[83,12719,12721],{"className":12720},[2269],[83,12722,12724,12744],{"className":12723},[2273,2274],[83,12725,12727,12741],{"className":12726},[2278],[83,12728,12730],{"className":12729,"style":2283},[2282],[83,12731,12732,12735],{"style":2286},[83,12733],{"className":12734,"style":2291},[2290],[83,12736,12738],{"className":12737},[2295,2296,2297,2298],[83,12739,1161],{"className":12740},[2234,2298],[83,12742,2306],{"className":12743},[2305],[83,12745,12747],{"className":12746},[2278],[83,12748,12750],{"className":12749,"style":2313},[2282],[83,12751],{},[83,12753],{"className":12754,"style":2243},[2242],[83,12756,229],{"className":12757},[2247],[83,12759],{"className":12760,"style":2243},[2242],[83,12762,12764,12767],{"className":12763},[2225],[83,12765],{"className":12766,"style":11012},[2229],[83,12768,12770,12773,13172],{"className":12769},[2234],[83,12771],{"className":12772},[6254,9342],[83,12774,12776],{"className":12775},[9249],[83,12777,12779,13164],{"className":12778},[2273,2274],[83,12780,12782,13161],{"className":12781},[2278],[83,12783,12785,12946,12954],{"className":12784,"style":11031},[2282],[83,12786,12787,12790],{"style":9358},[83,12788],{"className":12789,"style":2414},[2290],[83,12791,12793,12796,12799,12802,12805,12856,12859,12862,12865,12868,12871,12874,12877,12917],{"className":12792},[2234],[83,12794,313],{"className":12795},[2234,2264],[83,12797],{"className":12798,"style":6304},[2242],[83,12800,9260],{"className":12801,"style":11050},[9412,9457,11049],[83,12803,187],{"className":12804},[6254],[83,12806,12808,12811],{"className":12807},[2234],[83,12809,1640],{"className":12810},[2234,2264],[83,12812,12814],{"className":12813},[2269],[83,12815,12817,12848],{"className":12816},[2273,2274],[83,12818,12820,12845],{"className":12819},[2278],[83,12821,12823,12834],{"className":12822,"style":11072},[2282],[83,12824,12825,12828],{"style":11075},[83,12826],{"className":12827,"style":2291},[2290],[83,12829,12831],{"className":12830},[2295,2296,2297,2298],[83,12832,6578],{"className":12833},[2234,2264,2298],[83,12835,12836,12839],{"style":11087},[83,12837],{"className":12838,"style":2291},[2290],[83,12840,12842],{"className":12841},[2295,2296,2297,2298],[83,12843,1149],{"className":12844},[2234,2298],[83,12846,2306],{"className":12847},[2305],[83,12849,12851],{"className":12850},[2278],[83,12852,12854],{"className":12853,"style":11106},[2282],[83,12855],{},[83,12857,534],{"className":12858},[6350],[83,12860],{"className":12861,"style":2319},[2242],[83,12863,8650],{"className":12864},[2323],[83,12866],{"className":12867,"style":2319},[2242],[83,12869,187],{"className":12870},[6254],[83,12872,9260],{"className":12873,"style":11050},[9412,9457,11049],[83,12875],{"className":12876,"style":6304},[2242],[83,12878,12880,12883],{"className":12879},[2234],[83,12881,1640],{"className":12882},[2234,2264],[83,12884,12886],{"className":12885},[2269],[83,12887,12889,12909],{"className":12888},[2273,2274],[83,12890,12892,12906],{"className":12891},[2278],[83,12893,12895],{"className":12894,"style":6610},[2282],[83,12896,12897,12900],{"style":6276},[83,12898],{"className":12899,"style":2291},[2290],[83,12901,12903],{"className":12902},[2295,2296,2297,2298],[83,12904,6578],{"className":12905},[2234,2264,2298],[83,12907,2306],{"className":12908},[2305],[83,12910,12912],{"className":12911},[2278],[83,12913,12915],{"className":12914,"style":2313},[2282],[83,12916],{},[83,12918,12920,12923],{"className":12919},[6350],[83,12921,534],{"className":12922},[6350],[83,12924,12926],{"className":12925},[2269],[83,12927,12929],{"className":12928},[2273],[83,12930,12932],{"className":12931},[2278],[83,12933,12935],{"className":12934,"style":11188},[2282],[83,12936,12937,12940],{"style":11191},[83,12938],{"className":12939,"style":2291},[2290],[83,12941,12943],{"className":12942},[2295,2296,2297,2298],[83,12944,1149],{"className":12945},[2234,2298],[83,12947,12948,12951],{"style":9370},[83,12949],{"className":12950,"style":2414},[2290],[83,12952],{"className":12953,"style":9378},[9377],[83,12955,12956,12959],{"style":9381},[83,12957],{"className":12958,"style":2414},[2290],[83,12960,12962,12965,12968,12971,12974,13014,13054,13057,13060,13063,13066,13069,13072,13112,13115,13118,13121],{"className":12961},[2234],[83,12963,313],{"className":12964},[2234,2264],[83,12966],{"className":12967,"style":6304},[2242],[83,12969,9260],{"className":12970,"style":11050},[9412,9457,11049],[83,12972,187],{"className":12973},[6254],[83,12975,12977,12980],{"className":12976},[2234],[83,12978,1640],{"className":12979},[2234,2264],[83,12981,12983],{"className":12982},[2269],[83,12984,12986,13006],{"className":12985},[2273,2274],[83,12987,12989,13003],{"className":12988},[2278],[83,12990,12992],{"className":12991,"style":6610},[2282],[83,12993,12994,12997],{"style":6276},[83,12995],{"className":12996,"style":2291},[2290],[83,12998,13000],{"className":12999},[2295,2296,2297,2298],[83,13001,6578],{"className":13002},[2234,2264,2298],[83,13004,2306],{"className":13005},[2305],[83,13007,13009],{"className":13008},[2278],[83,13010,13012],{"className":13011,"style":2313},[2282],[83,13013],{},[83,13015,13017,13020],{"className":13016},[2234],[83,13018,3972],{"className":13019,"style":6311},[2234,2264],[83,13021,13023],{"className":13022},[2269],[83,13024,13026,13046],{"className":13025},[2273,2274],[83,13027,13029,13043],{"className":13028},[2278],[83,13030,13032],{"className":13031,"style":6610},[2282],[83,13033,13034,13037],{"style":6326},[83,13035],{"className":13036,"style":2291},[2290],[83,13038,13040],{"className":13039},[2295,2296,2297,2298],[83,13041,6578],{"className":13042},[2234,2264,2298],[83,13044,2306],{"className":13045},[2305],[83,13047,13049],{"className":13048},[2278],[83,13050,13052],{"className":13051,"style":2313},[2282],[83,13053],{},[83,13055,534],{"className":13056},[6350],[83,13058],{"className":13059,"style":2319},[2242],[83,13061,8650],{"className":13062},[2323],[83,13064],{"className":13065,"style":2319},[2242],[83,13067,9260],{"className":13068,"style":11050},[9412,9457,11049],[83,13070],{"className":13071,"style":6304},[2242],[83,13073,13075,13078],{"className":13074},[2234],[83,13076,1640],{"className":13077},[2234,2264],[83,13079,13081],{"className":13080},[2269],[83,13082,13084,13104],{"className":13083},[2273,2274],[83,13085,13087,13101],{"className":13086},[2278],[83,13088,13090],{"className":13089,"style":6610},[2282],[83,13091,13092,13095],{"style":6276},[83,13093],{"className":13094,"style":2291},[2290],[83,13096,13098],{"className":13097},[2295,2296,2297,2298],[83,13099,6578],{"className":13100},[2234,2264,2298],[83,13102,2306],{"className":13103},[2305],[83,13105,13107],{"className":13106},[2278],[83,13108,13110],{"className":13109,"style":2313},[2282],[83,13111],{},[83,13113],{"className":13114,"style":6304},[2242],[83,13116,9260],{"className":13117,"style":11050},[9412,9457,11049],[83,13119],{"className":13120,"style":6304},[2242],[83,13122,13124,13127],{"className":13123},[2234],[83,13125,3972],{"className":13126,"style":6311},[2234,2264],[83,13128,13130],{"className":13129},[2269],[83,13131,13133,13153],{"className":13132},[2273,2274],[83,13134,13136,13150],{"className":13135},[2278],[83,13137,13139],{"className":13138,"style":6610},[2282],[83,13140,13141,13144],{"style":6326},[83,13142],{"className":13143,"style":2291},[2290],[83,13145,13147],{"className":13146},[2295,2296,2297,2298],[83,13148,6578],{"className":13149},[2234,2264,2298],[83,13151,2306],{"className":13152},[2305],[83,13154,13156],{"className":13155},[2278],[83,13157,13159],{"className":13158,"style":2313},[2282],[83,13160],{},[83,13162,2306],{"className":13163},[2305],[83,13165,13167],{"className":13166},[2278],[83,13168,13170],{"className":13169,"style":11425},[2282],[83,13171],{},[83,13173],{"className":13174},[6350,9342],[83,13176,13178],{"className":13177},[2147],[83,13179,13181,13220],{"className":13180},[2151],[83,13182,13184],{"className":13183},[2155],[2157,13185,13186],{"xmlns":2159,"display":2160},[2162,13187,13188,13218],{},[2165,13189,13190,13196,13198,13204,13206,13212],{},[2175,13191,13192,13194],{},[2178,13193,2180],{},[2182,13195,411],{},[2172,13197,229],{},[2202,13199,13200,13202],{"accent":2204},[2178,13201,3972],{},[2172,13203,11460],{},[2172,13205,8650],{},[2175,13207,13208,13210],{},[2178,13209,2180],{},[2182,13211,1161],{},[2202,13213,13214,13216],{"accent":2204},[2178,13215,1640],{},[2172,13217,11460],{},[2214,13219,11477],{"encoding":2216},[83,13221,13223,13278,13335],{"className":13222,"ariaHidden":2204},[2221],[83,13224,13226,13229,13269,13272,13275],{"className":13225},[2225],[83,13227],{"className":13228,"style":2257},[2229],[83,13230,13232,13235],{"className":13231},[2234],[83,13233,2180],{"className":13234,"style":2265},[2234,2264],[83,13236,13238],{"className":13237},[2269],[83,13239,13241,13261],{"className":13240},[2273,2274],[83,13242,13244,13258],{"className":13243},[2278],[83,13245,13247],{"className":13246,"style":2283},[2282],[83,13248,13249,13252],{"style":2286},[83,13250],{"className":13251,"style":2291},[2290],[83,13253,13255],{"className":13254},[2295,2296,2297,2298],[83,13256,411],{"className":13257},[2234,2298],[83,13259,2306],{"className":13260},[2305],[83,13262,13264],{"className":13263},[2278],[83,13265,13267],{"className":13266,"style":2313},[2282],[83,13268],{},[83,13270],{"className":13271,"style":2243},[2242],[83,13273,229],{"className":13274},[2247],[83,13276],{"className":13277,"style":2243},[2242],[83,13279,13281,13284,13326,13329,13332],{"className":13280},[2225],[83,13282],{"className":13283,"style":8737},[2229],[83,13285,13287],{"className":13286},[2234,2398],[83,13288,13290,13318],{"className":13289},[2273,2274],[83,13291,13293,13315],{"className":13292},[2278],[83,13294,13296,13304],{"className":13295,"style":11554},[2282],[83,13297,13298,13301],{"style":2410},[83,13299],{"className":13300,"style":2414},[2290],[83,13302,3972],{"className":13303,"style":6311},[2234,2264],[83,13305,13306,13309],{"style":2410},[83,13307],{"className":13308,"style":2414},[2290],[83,13310,13312],{"className":13311,"style":9858},[2426],[83,13313,11460],{"className":13314},[2234],[83,13316,2306],{"className":13317},[2305],[83,13319,13321],{"className":13320},[2278],[83,13322,13324],{"className":13323,"style":8875},[2282],[83,13325],{},[83,13327],{"className":13328,"style":2319},[2242],[83,13330,8650],{"className":13331},[2323],[83,13333],{"className":13334,"style":2319},[2242],[83,13336,13338,13341,13381],{"className":13337},[2225],[83,13339],{"className":13340,"style":2257},[2229],[83,13342,13344,13347],{"className":13343},[2234],[83,13345,2180],{"className":13346,"style":2265},[2234,2264],[83,13348,13350],{"className":13349},[2269],[83,13351,13353,13373],{"className":13352},[2273,2274],[83,13354,13356,13370],{"className":13355},[2278],[83,13357,13359],{"className":13358,"style":2283},[2282],[83,13360,13361,13364],{"style":2286},[83,13362],{"className":13363,"style":2291},[2290],[83,13365,13367],{"className":13366},[2295,2296,2297,2298],[83,13368,1161],{"className":13369},[2234,2298],[83,13371,2306],{"className":13372},[2305],[83,13374,13376],{"className":13375},[2278],[83,13377,13379],{"className":13378,"style":2313},[2282],[83,13380],{},[83,13382,13384],{"className":13383},[2234,2398],[83,13385,13387],{"className":13386},[2273],[83,13388,13390],{"className":13389},[2278],[83,13391,13393,13401],{"className":13392,"style":11554},[2282],[83,13394,13395,13398],{"style":2410},[83,13396],{"className":13397,"style":2414},[2290],[83,13399,1640],{"className":13400},[2234,2264],[83,13402,13403,13406],{"style":2410},[83,13404],{"className":13405,"style":2414},[2290],[83,13407,13409],{"className":13408,"style":11668},[2426],[83,13410,11460],{"className":13411},[2234],[12,13413,7598],{},[1359,13415,13416,13447,13588],{},[1362,13417,13418,13446],{},[83,13419,13421,13434],{"className":13420},[2151],[83,13422,13424],{"className":13423},[2155],[2157,13425,13426],{"xmlns":2159},[2162,13427,13428,13432],{},[2165,13429,13430],{},[2178,13431,313],{},[2214,13433,313],{"encoding":2216},[83,13435,13437],{"className":13436,"ariaHidden":2204},[2221],[83,13438,13440,13443],{"className":13439},[2225],[83,13441],{"className":13442,"style":7592},[2229],[83,13444,313],{"className":13445},[2234,2264]," es el número de ejemplos (en este caso, 3).",[1362,13448,13449,1966,13518,13587],{},[83,13450,13452,13469],{"className":13451},[2151],[83,13453,13455],{"className":13454},[2155],[2157,13456,13457],{"xmlns":2159},[2162,13458,13459,13467],{},[2165,13460,13461],{},[2175,13462,13463,13465],{},[2178,13464,1640],{},[2178,13466,6578],{},[2214,13468,6581],{"encoding":2216},[83,13470,13472],{"className":13471,"ariaHidden":2204},[2221],[83,13473,13475,13478],{"className":13474},[2225],[83,13476],{"className":13477,"style":6591},[2229],[83,13479,13481,13484],{"className":13480},[2234],[83,13482,1640],{"className":13483},[2234,2264],[83,13485,13487],{"className":13486},[2269],[83,13488,13490,13510],{"className":13489},[2273,2274],[83,13491,13493,13507],{"className":13492},[2278],[83,13494,13496],{"className":13495,"style":6610},[2282],[83,13497,13498,13501],{"style":6276},[83,13499],{"className":13500,"style":2291},[2290],[83,13502,13504],{"className":13503},[2295,2296,2297,2298],[83,13505,6578],{"className":13506},[2234,2264,2298],[83,13508,2306],{"className":13509},[2305],[83,13511,13513],{"className":13512},[2278],[83,13514,13516],{"className":13515,"style":2313},[2282],[83,13517],{},[83,13519,13521,13538],{"className":13520},[2151],[83,13522,13524],{"className":13523},[2155],[2157,13525,13526],{"xmlns":2159},[2162,13527,13528,13536],{},[2165,13529,13530],{},[2175,13531,13532,13534],{},[2178,13533,3972],{},[2178,13535,6578],{},[2214,13537,6654],{"encoding":2216},[83,13539,13541],{"className":13540,"ariaHidden":2204},[2221],[83,13542,13544,13547],{"className":13543},[2225],[83,13545],{"className":13546,"style":6664},[2229],[83,13548,13550,13553],{"className":13549},[2234],[83,13551,3972],{"className":13552,"style":6311},[2234,2264],[83,13554,13556],{"className":13555},[2269],[83,13557,13559,13579],{"className":13558},[2273,2274],[83,13560,13562,13576],{"className":13561},[2278],[83,13563,13565],{"className":13564,"style":6610},[2282],[83,13566,13567,13570],{"style":6326},[83,13568],{"className":13569,"style":2291},[2290],[83,13571,13573],{"className":13572},[2295,2296,2297,2298],[83,13574,6578],{"className":13575},[2234,2264,2298],[83,13577,2306],{"className":13578},[2305],[83,13580,13582],{"className":13581},[2278],[83,13583,13585],{"className":13584,"style":2313},[2282],[83,13586],{}," son los valores de tamaño y precio para cada ejemplo.",[1362,13589,13590,1966,13650,13721],{},[83,13591,13593,13610],{"className":13592},[2151],[83,13594,13596],{"className":13595},[2155],[2157,13597,13598],{"xmlns":2159},[2162,13599,13600,13608],{},[2165,13601,13602],{},[2202,13603,13604,13606],{"accent":2204},[2178,13605,1640],{},[2172,13607,11460],{},[2214,13609,11869],{"encoding":2216},[83,13611,13613],{"className":13612,"ariaHidden":2204},[2221],[83,13614,13616,13619],{"className":13615},[2225],[83,13617],{"className":13618,"style":11554},[2229],[83,13620,13622],{"className":13621},[2234,2398],[83,13623,13625],{"className":13624},[2273],[83,13626,13628],{"className":13627},[2278],[83,13629,13631,13639],{"className":13630,"style":11554},[2282],[83,13632,13633,13636],{"style":2410},[83,13634],{"className":13635,"style":2414},[2290],[83,13637,1640],{"className":13638},[2234,2264],[83,13640,13641,13644],{"style":2410},[83,13642],{"className":13643,"style":2414},[2290],[83,13645,13647],{"className":13646,"style":11668},[2426],[83,13648,11460],{"className":13649},[2234],[83,13651,13653,13670],{"className":13652},[2151],[83,13654,13656],{"className":13655},[2155],[2157,13657,13658],{"xmlns":2159},[2162,13659,13660,13668],{},[2165,13661,13662],{},[2202,13663,13664,13666],{"accent":2204},[2178,13665,3972],{},[2172,13667,11460],{},[2214,13669,11930],{"encoding":2216},[83,13671,13673],{"className":13672,"ariaHidden":2204},[2221],[83,13674,13676,13679],{"className":13675},[2225],[83,13677],{"className":13678,"style":11940},[2229],[83,13680,13682],{"className":13681},[2234,2398],[83,13683,13685,13713],{"className":13684},[2273,2274],[83,13686,13688,13710],{"className":13687},[2278],[83,13689,13691,13699],{"className":13690,"style":11554},[2282],[83,13692,13693,13696],{"style":2410},[83,13694],{"className":13695,"style":2414},[2290],[83,13697,3972],{"className":13698,"style":6311},[2234,2264],[83,13700,13701,13704],{"style":2410},[83,13702],{"className":13703,"style":2414},[2290],[83,13705,13707],{"className":13706,"style":9858},[2426],[83,13708,11460],{"className":13709},[2234],[83,13711,2306],{"className":13712},[2305],[83,13714,13716],{"className":13715},[2278],[83,13717,13719],{"className":13718,"style":8875},[2282],[83,13720],{}," son las medias de las variables independientes y dependientes, respectivamente.",[12,13723,13724],{},"Tenemos entonces para este caso:",[83,13726,13728],{"className":13727},[2147],[83,13729,13731,13867],{"className":13730},[2151],[83,13732,13734],{"className":13733},[2155],[2157,13735,13736],{"xmlns":2159,"display":2160},[2162,13737,13738,13864],{},[2165,13739,13740,13746,13748],{},[2175,13741,13742,13744],{},[2178,13743,2180],{},[2182,13745,1161],{},[2172,13747,229],{},[9249,13749,13750,13814],{},[2165,13751,13752,13754,13756,13758,13761,13764,13766,13768,13770,13773,13775,13777,13779,13782,13784,13786,13788,13790,13792,13794,13796,13798,13800,13802,13804,13806,13808,13810,13812],{},[2182,13753,1137],{},[2172,13755,187],{"stretchy":6169},[2182,13757,12005],{},[2172,13759,13760],{},"∗",[2182,13762,13763],{},"100000",[2172,13765,2186],{},[2182,13767,12013],{},[2172,13769,13760],{},[2182,13771,13772],{},"200000",[2172,13774,2186],{},[2182,13776,12021],{},[2172,13778,13760],{},[2182,13780,13781],{},"300000",[2172,13783,534],{"stretchy":6169},[2172,13785,8650],{},[2172,13787,187],{"stretchy":6169},[2182,13789,12005],{},[2172,13791,2186],{},[2182,13793,12013],{},[2172,13795,2186],{},[2182,13797,12021],{},[2172,13799,534],{"stretchy":6169},[2172,13801,187],{"stretchy":6169},[2182,13803,13763],{},[2172,13805,2186],{},[2182,13807,13772],{},[2172,13809,2186],{},[2182,13811,13781],{},[2172,13813,534],{"stretchy":6169},[2165,13815,13816,13818,13820,13826,13828,13834,13836,13842,13844,13846,13848,13850,13852,13854,13856,13858],{},[2182,13817,1137],{},[2172,13819,187],{"stretchy":6169},[3702,13821,13822,13824],{},[2182,13823,12005],{},[2182,13825,1149],{},[2172,13827,2186],{},[3702,13829,13830,13832],{},[2182,13831,12013],{},[2182,13833,1149],{},[2172,13835,2186],{},[3702,13837,13838,13840],{},[2182,13839,12021],{},[2182,13841,1149],{},[2172,13843,534],{"stretchy":6169},[2172,13845,8650],{},[2172,13847,187],{"stretchy":6169},[2182,13849,12005],{},[2172,13851,2186],{},[2182,13853,12013],{},[2172,13855,2186],{},[2182,13857,12021],{},[3702,13859,13860,13862],{},[2172,13861,534],{"stretchy":6169},[2182,13863,1149],{},[2214,13865,13866],{"encoding":2216},"\\beta_1 = \\frac{3(50*100000 + 100*200000 + 150*300000) - (50 + 100 + 150)(100000 + 200000 + 300000)}{3(50^2 + 100^2 + 150^2) - (50 + 100 + 150)^2}",[83,13868,13870,13925],{"className":13869,"ariaHidden":2204},[2221],[83,13871,13873,13876,13916,13919,13922],{"className":13872},[2225],[83,13874],{"className":13875,"style":2257},[2229],[83,13877,13879,13882],{"className":13878},[2234],[83,13880,2180],{"className":13881,"style":2265},[2234,2264],[83,13883,13885],{"className":13884},[2269],[83,13886,13888,13908],{"className":13887},[2273,2274],[83,13889,13891,13905],{"className":13890},[2278],[83,13892,13894],{"className":13893,"style":2283},[2282],[83,13895,13896,13899],{"style":2286},[83,13897],{"className":13898,"style":2291},[2290],[83,13900,13902],{"className":13901},[2295,2296,2297,2298],[83,13903,1161],{"className":13904},[2234,2298],[83,13906,2306],{"className":13907},[2305],[83,13909,13911],{"className":13910},[2278],[83,13912,13914],{"className":13913,"style":2313},[2282],[83,13915],{},[83,13917],{"className":13918,"style":2243},[2242],[83,13920,229],{"className":13921},[2247],[83,13923],{"className":13924,"style":2243},[2242],[83,13926,13928,13932],{"className":13927},[2225],[83,13929],{"className":13930,"style":13931},[2229],"height:2.363em;vertical-align:-0.936em;",[83,13933,13935,13938,14326],{"className":13934},[2234],[83,13936],{"className":13937},[6254,9342],[83,13939,13941],{"className":13940},[9249],[83,13942,13944,14317],{"className":13943},[2273,2274],[83,13945,13947,14314],{"className":13946},[2278],[83,13948,13950,14151,14159],{"className":13949,"style":11031},[2282],[83,13951,13952,13955],{"style":9358},[83,13953],{"className":13954,"style":2414},[2290],[83,13956,13958,13961,13964,13967,13996,13999,14002,14005,14009,14038,14041,14044,14047,14051,14080,14083,14086,14089,14092,14095,14098,14101,14104,14107,14110,14113,14116,14119,14122],{"className":13957},[2234],[83,13959,1137],{"className":13960},[2234],[83,13962,187],{"className":13963},[6254],[83,13965,1461],{"className":13966},[2234],[83,13968,13970,13973],{"className":13969},[2234],[83,13971,411],{"className":13972},[2234],[83,13974,13976],{"className":13975},[2269],[83,13977,13979],{"className":13978},[2273],[83,13980,13982],{"className":13981},[2278],[83,13983,13985],{"className":13984,"style":11188},[2282],[83,13986,13987,13990],{"style":11191},[83,13988],{"className":13989,"style":2291},[2290],[83,13991,13993],{"className":13992},[2295,2296,2297,2298],[83,13994,1149],{"className":13995},[2234,2298],[83,13997],{"className":13998,"style":2319},[2242],[83,14000,2186],{"className":14001},[2323],[83,14003],{"className":14004,"style":2319},[2242],[83,14006,14008],{"className":14007},[2234],"10",[83,14010,14012,14015],{"className":14011},[2234],[83,14013,411],{"className":14014},[2234],[83,14016,14018],{"className":14017},[2269],[83,14019,14021],{"className":14020},[2273],[83,14022,14024],{"className":14023},[2278],[83,14025,14027],{"className":14026,"style":11188},[2282],[83,14028,14029,14032],{"style":11191},[83,14030],{"className":14031,"style":2291},[2290],[83,14033,14035],{"className":14034},[2295,2296,2297,2298],[83,14036,1149],{"className":14037},[2234,2298],[83,14039],{"className":14040,"style":2319},[2242],[83,14042,2186],{"className":14043},[2323],[83,14045],{"className":14046,"style":2319},[2242],[83,14048,14050],{"className":14049},[2234],"15",[83,14052,14054,14057],{"className":14053},[2234],[83,14055,411],{"className":14056},[2234],[83,14058,14060],{"className":14059},[2269],[83,14061,14063],{"className":14062},[2273],[83,14064,14066],{"className":14065},[2278],[83,14067,14069],{"className":14068,"style":11188},[2282],[83,14070,14071,14074],{"style":11191},[83,14072],{"className":14073,"style":2291},[2290],[83,14075,14077],{"className":14076},[2295,2296,2297,2298],[83,14078,1149],{"className":14079},[2234,2298],[83,14081,534],{"className":14082},[6350],[83,14084],{"className":14085,"style":2319},[2242],[83,14087,8650],{"className":14088},[2323],[83,14090],{"className":14091,"style":2319},[2242],[83,14093,187],{"className":14094},[6254],[83,14096,12005],{"className":14097},[2234],[83,14099],{"className":14100,"style":2319},[2242],[83,14102,2186],{"className":14103},[2323],[83,14105],{"className":14106,"style":2319},[2242],[83,14108,12013],{"className":14109},[2234],[83,14111],{"className":14112,"style":2319},[2242],[83,14114,2186],{"className":14115},[2323],[83,14117],{"className":14118,"style":2319},[2242],[83,14120,12021],{"className":14121},[2234],[83,14123,14125,14128],{"className":14124},[6350],[83,14126,534],{"className":14127},[6350],[83,14129,14131],{"className":14130},[2269],[83,14132,14134],{"className":14133},[2273],[83,14135,14137],{"className":14136},[2278],[83,14138,14140],{"className":14139,"style":11188},[2282],[83,14141,14142,14145],{"style":11191},[83,14143],{"className":14144,"style":2291},[2290],[83,14146,14148],{"className":14147},[2295,2296,2297,2298],[83,14149,1149],{"className":14150},[2234,2298],[83,14152,14153,14156],{"style":9370},[83,14154],{"className":14155,"style":2414},[2290],[83,14157],{"className":14158,"style":9378},[9377],[83,14160,14161,14164],{"style":9381},[83,14162],{"className":14163,"style":2414},[2290],[83,14165,14167,14170,14173,14176,14179,14182,14185,14188,14191,14194,14197,14200,14203,14206,14209,14212,14215,14218,14221,14224,14227,14230,14233,14236,14239,14242,14245,14248,14251,14254,14257,14260,14263,14266,14269,14272,14275,14278,14281,14284,14287,14290,14293,14296,14299,14302,14305,14308,14311],{"className":14166},[2234],[83,14168,1137],{"className":14169},[2234],[83,14171,187],{"className":14172},[6254],[83,14174,12005],{"className":14175},[2234],[83,14177],{"className":14178,"style":2319},[2242],[83,14180,13760],{"className":14181},[2323],[83,14183],{"className":14184,"style":2319},[2242],[83,14186,13763],{"className":14187},[2234],[83,14189],{"className":14190,"style":2319},[2242],[83,14192,2186],{"className":14193},[2323],[83,14195],{"className":14196,"style":2319},[2242],[83,14198,12013],{"className":14199},[2234],[83,14201],{"className":14202,"style":2319},[2242],[83,14204,13760],{"className":14205},[2323],[83,14207],{"className":14208,"style":2319},[2242],[83,14210,13772],{"className":14211},[2234],[83,14213],{"className":14214,"style":2319},[2242],[83,14216,2186],{"className":14217},[2323],[83,14219],{"className":14220,"style":2319},[2242],[83,14222,12021],{"className":14223},[2234],[83,14225],{"className":14226,"style":2319},[2242],[83,14228,13760],{"className":14229},[2323],[83,14231],{"className":14232,"style":2319},[2242],[83,14234,13781],{"className":14235},[2234],[83,14237,534],{"className":14238},[6350],[83,14240],{"className":14241,"style":2319},[2242],[83,14243,8650],{"className":14244},[2323],[83,14246],{"className":14247,"style":2319},[2242],[83,14249,187],{"className":14250},[6254],[83,14252,12005],{"className":14253},[2234],[83,14255],{"className":14256,"style":2319},[2242],[83,14258,2186],{"className":14259},[2323],[83,14261],{"className":14262,"style":2319},[2242],[83,14264,12013],{"className":14265},[2234],[83,14267],{"className":14268,"style":2319},[2242],[83,14270,2186],{"className":14271},[2323],[83,14273],{"className":14274,"style":2319},[2242],[83,14276,12021],{"className":14277},[2234],[83,14279,534],{"className":14280},[6350],[83,14282,187],{"className":14283},[6254],[83,14285,13763],{"className":14286},[2234],[83,14288],{"className":14289,"style":2319},[2242],[83,14291,2186],{"className":14292},[2323],[83,14294],{"className":14295,"style":2319},[2242],[83,14297,13772],{"className":14298},[2234],[83,14300],{"className":14301,"style":2319},[2242],[83,14303,2186],{"className":14304},[2323],[83,14306],{"className":14307,"style":2319},[2242],[83,14309,13781],{"className":14310},[2234],[83,14312,534],{"className":14313},[6350],[83,14315,2306],{"className":14316},[2305],[83,14318,14320],{"className":14319},[2278],[83,14321,14324],{"className":14322,"style":14323},[2282],"height:0.936em;",[83,14325],{},[83,14327],{"className":14328},[6350,9342],[83,14330,14332],{"className":14331},[2147],[83,14333,14335,14395],{"className":14334},[2151],[83,14336,14338],{"className":14337},[2155],[2157,14339,14340],{"xmlns":2159,"display":2160},[2162,14341,14342,14392],{},[2165,14343,14344,14350,14352,14368,14370,14376],{},[2175,14345,14346,14348],{},[2178,14347,2180],{},[2182,14349,411],{},[2172,14351,229],{},[9249,14353,14354,14366],{},[2165,14355,14356,14358,14360,14362,14364],{},[2182,14357,13763],{},[2172,14359,2186],{},[2182,14361,13772],{},[2172,14363,2186],{},[2182,14365,13781],{},[2182,14367,1137],{},[2172,14369,8650],{},[2175,14371,14372,14374],{},[2178,14373,2180],{},[2182,14375,1161],{},[9249,14377,14378,14390],{},[2165,14379,14380,14382,14384,14386,14388],{},[2182,14381,12005],{},[2172,14383,2186],{},[2182,14385,12013],{},[2172,14387,2186],{},[2182,14389,12021],{},[2182,14391,1137],{},[2214,14393,14394],{"encoding":2216},"\\beta_0 = \\frac{100000 + 200000 + 300000}{3} - \\beta_1 \\frac{50 + 100 + 150}{3}",[83,14396,14398,14453,14555],{"className":14397,"ariaHidden":2204},[2221],[83,14399,14401,14404,14444,14447,14450],{"className":14400},[2225],[83,14402],{"className":14403,"style":2257},[2229],[83,14405,14407,14410],{"className":14406},[2234],[83,14408,2180],{"className":14409,"style":2265},[2234,2264],[83,14411,14413],{"className":14412},[2269],[83,14414,14416,14436],{"className":14415},[2273,2274],[83,14417,14419,14433],{"className":14418},[2278],[83,14420,14422],{"className":14421,"style":2283},[2282],[83,14423,14424,14427],{"style":2286},[83,14425],{"className":14426,"style":2291},[2290],[83,14428,14430],{"className":14429},[2295,2296,2297,2298],[83,14431,411],{"className":14432},[2234,2298],[83,14434,2306],{"className":14435},[2305],[83,14437,14439],{"className":14438},[2278],[83,14440,14442],{"className":14441,"style":2313},[2282],[83,14443],{},[83,14445],{"className":14446,"style":2243},[2242],[83,14448,229],{"className":14449},[2247],[83,14451],{"className":14452,"style":2243},[2242],[83,14454,14456,14460,14546,14549,14552],{"className":14455},[2225],[83,14457],{"className":14458,"style":14459},[2229],"height:2.0074em;vertical-align:-0.686em;",[83,14461,14463,14466,14543],{"className":14462},[2234],[83,14464],{"className":14465},[6254,9342],[83,14467,14469],{"className":14468},[9249],[83,14470,14472,14535],{"className":14471},[2273,2274],[83,14473,14475,14532],{"className":14474},[2278],[83,14476,14478,14489,14497],{"className":14477,"style":9355},[2282],[83,14479,14480,14483],{"style":9358},[83,14481],{"className":14482,"style":2414},[2290],[83,14484,14486],{"className":14485},[2234],[83,14487,1137],{"className":14488},[2234],[83,14490,14491,14494],{"style":9370},[83,14492],{"className":14493,"style":2414},[2290],[83,14495],{"className":14496,"style":9378},[9377],[83,14498,14499,14502],{"style":9381},[83,14500],{"className":14501,"style":2414},[2290],[83,14503,14505,14508,14511,14514,14517,14520,14523,14526,14529],{"className":14504},[2234],[83,14506,13763],{"className":14507},[2234],[83,14509],{"className":14510,"style":2319},[2242],[83,14512,2186],{"className":14513},[2323],[83,14515],{"className":14516,"style":2319},[2242],[83,14518,13772],{"className":14519},[2234],[83,14521],{"className":14522,"style":2319},[2242],[83,14524,2186],{"className":14525},[2323],[83,14527],{"className":14528,"style":2319},[2242],[83,14530,13781],{"className":14531},[2234],[83,14533,2306],{"className":14534},[2305],[83,14536,14538],{"className":14537},[2278],[83,14539,14541],{"className":14540,"style":9400},[2282],[83,14542],{},[83,14544],{"className":14545},[6350,9342],[83,14547],{"className":14548,"style":2319},[2242],[83,14550,8650],{"className":14551},[2323],[83,14553],{"className":14554,"style":2319},[2242],[83,14556,14558,14561,14601],{"className":14557},[2225],[83,14559],{"className":14560,"style":14459},[2229],[83,14562,14564,14567],{"className":14563},[2234],[83,14565,2180],{"className":14566,"style":2265},[2234,2264],[83,14568,14570],{"className":14569},[2269],[83,14571,14573,14593],{"className":14572},[2273,2274],[83,14574,14576,14590],{"className":14575},[2278],[83,14577,14579],{"className":14578,"style":2283},[2282],[83,14580,14581,14584],{"style":2286},[83,14582],{"className":14583,"style":2291},[2290],[83,14585,14587],{"className":14586},[2295,2296,2297,2298],[83,14588,1161],{"className":14589},[2234,2298],[83,14591,2306],{"className":14592},[2305],[83,14594,14596],{"className":14595},[2278],[83,14597,14599],{"className":14598,"style":2313},[2282],[83,14600],{},[83,14602,14604,14607,14684],{"className":14603},[2234],[83,14605],{"className":14606},[6254,9342],[83,14608,14610],{"className":14609},[9249],[83,14611,14613,14676],{"className":14612},[2273,2274],[83,14614,14616,14673],{"className":14615},[2278],[83,14617,14619,14630,14638],{"className":14618,"style":9355},[2282],[83,14620,14621,14624],{"style":9358},[83,14622],{"className":14623,"style":2414},[2290],[83,14625,14627],{"className":14626},[2234],[83,14628,1137],{"className":14629},[2234],[83,14631,14632,14635],{"style":9370},[83,14633],{"className":14634,"style":2414},[2290],[83,14636],{"className":14637,"style":9378},[9377],[83,14639,14640,14643],{"style":9381},[83,14641],{"className":14642,"style":2414},[2290],[83,14644,14646,14649,14652,14655,14658,14661,14664,14667,14670],{"className":14645},[2234],[83,14647,12005],{"className":14648},[2234],[83,14650],{"className":14651,"style":2319},[2242],[83,14653,2186],{"className":14654},[2323],[83,14656],{"className":14657,"style":2319},[2242],[83,14659,12013],{"className":14660},[2234],[83,14662],{"className":14663,"style":2319},[2242],[83,14665,2186],{"className":14666},[2323],[83,14668],{"className":14669,"style":2319},[2242],[83,14671,12021],{"className":14672},[2234],[83,14674,2306],{"className":14675},[2305],[83,14677,14679],{"className":14678},[2278],[83,14680,14682],{"className":14681,"style":9400},[2282],[83,14683],{},[83,14685],{"className":14686},[6350,9342],[12,14688,14689,14690,1966,14783,14876],{},"Resolviendo estas fórmulas, obtenemos los valores de ",[83,14691,14693,14715],{"className":14692},[2151],[83,14694,14696],{"className":14695},[2155],[2157,14697,14698],{"xmlns":2159},[2162,14699,14700,14712],{},[2165,14701,14702,14708,14710],{},[2175,14703,14704,14706],{},[2178,14705,2180],{},[2182,14707,411],{},[2172,14709,229],{},[2182,14711,411],{},[2214,14713,14714],{"encoding":2216},"\\beta_0 = 0",[83,14716,14718,14773],{"className":14717,"ariaHidden":2204},[2221],[83,14719,14721,14724,14764,14767,14770],{"className":14720},[2225],[83,14722],{"className":14723,"style":2257},[2229],[83,14725,14727,14730],{"className":14726},[2234],[83,14728,2180],{"className":14729,"style":2265},[2234,2264],[83,14731,14733],{"className":14732},[2269],[83,14734,14736,14756],{"className":14735},[2273,2274],[83,14737,14739,14753],{"className":14738},[2278],[83,14740,14742],{"className":14741,"style":2283},[2282],[83,14743,14744,14747],{"style":2286},[83,14745],{"className":14746,"style":2291},[2290],[83,14748,14750],{"className":14749},[2295,2296,2297,2298],[83,14751,411],{"className":14752},[2234,2298],[83,14754,2306],{"className":14755},[2305],[83,14757,14759],{"className":14758},[2278],[83,14760,14762],{"className":14761,"style":2313},[2282],[83,14763],{},[83,14765],{"className":14766,"style":2243},[2242],[83,14768,229],{"className":14769},[2247],[83,14771],{"className":14772,"style":2243},[2242],[83,14774,14776,14780],{"className":14775},[2225],[83,14777],{"className":14778,"style":14779},[2229],"height:0.6444em;",[83,14781,411],{"className":14782},[2234],[83,14784,14786,14809],{"className":14785},[2151],[83,14787,14789],{"className":14788},[2155],[2157,14790,14791],{"xmlns":2159},[2162,14792,14793,14806],{},[2165,14794,14795,14801,14803],{},[2175,14796,14797,14799],{},[2178,14798,2180],{},[2182,14800,1161],{},[2172,14802,229],{},[2182,14804,14805],{},"2000",[2214,14807,14808],{"encoding":2216},"\\beta_1 = 2000",[83,14810,14812,14867],{"className":14811,"ariaHidden":2204},[2221],[83,14813,14815,14818,14858,14861,14864],{"className":14814},[2225],[83,14816],{"className":14817,"style":2257},[2229],[83,14819,14821,14824],{"className":14820},[2234],[83,14822,2180],{"className":14823,"style":2265},[2234,2264],[83,14825,14827],{"className":14826},[2269],[83,14828,14830,14850],{"className":14829},[2273,2274],[83,14831,14833,14847],{"className":14832},[2278],[83,14834,14836],{"className":14835,"style":2283},[2282],[83,14837,14838,14841],{"style":2286},[83,14839],{"className":14840,"style":2291},[2290],[83,14842,14844],{"className":14843},[2295,2296,2297,2298],[83,14845,1161],{"className":14846},[2234,2298],[83,14848,2306],{"className":14849},[2305],[83,14851,14853],{"className":14852},[2278],[83,14854,14856],{"className":14855,"style":2313},[2282],[83,14857],{},[83,14859],{"className":14860,"style":2243},[2242],[83,14862,229],{"className":14863},[2247],[83,14865],{"className":14866,"style":2243},[2242],[83,14868,14870,14873],{"className":14869},[2225],[83,14871],{"className":14872,"style":14779},[2229],[83,14874,14805],{"className":14875},[2234],", que nos permiten construir el siguiente modelo:",[83,14878,14880],{"className":14879},[2147],[83,14881,14883,14911],{"className":14882},[2151],[83,14884,14886],{"className":14885},[2155],[2157,14887,14888],{"xmlns":2159,"display":2160},[2162,14889,14890,14908],{},[2165,14891,14892,14898,14900,14902,14904,14906],{},[2202,14893,14894,14896],{"accent":2204},[2178,14895,3972],{},[2172,14897,8661],{},[2172,14899,229],{},[2182,14901,411],{},[2172,14903,2186],{},[2182,14905,14805],{},[2178,14907,1640],{},[2214,14909,14910],{"encoding":2216},"\\hat{y} = 0 + 2000x",[83,14912,14914,14971,14990],{"className":14913,"ariaHidden":2204},[2221],[83,14915,14917,14920,14962,14965,14968],{"className":14916},[2225],[83,14918],{"className":14919,"style":2257},[2229],[83,14921,14923],{"className":14922},[2234,2398],[83,14924,14926,14954],{"className":14925},[2273,2274],[83,14927,14929,14951],{"className":14928},[2278],[83,14930,14932,14940],{"className":14931,"style":2388},[2282],[83,14933,14934,14937],{"style":2410},[83,14935],{"className":14936,"style":2414},[2290],[83,14938,3972],{"className":14939,"style":6311},[2234,2264],[83,14941,14942,14945],{"style":2410},[83,14943],{"className":14944,"style":2414},[2290],[83,14946,14948],{"className":14947,"style":9858},[2426],[83,14949,8661],{"className":14950},[2234],[83,14952,2306],{"className":14953},[2305],[83,14955,14957],{"className":14956},[2278],[83,14958,14960],{"className":14959,"style":8875},[2282],[83,14961],{},[83,14963],{"className":14964,"style":2243},[2242],[83,14966,229],{"className":14967},[2247],[83,14969],{"className":14970,"style":2243},[2242],[83,14972,14974,14978,14981,14984,14987],{"className":14973},[2225],[83,14975],{"className":14976,"style":14977},[2229],"height:0.7278em;vertical-align:-0.0833em;",[83,14979,411],{"className":14980},[2234],[83,14982],{"className":14983,"style":2319},[2242],[83,14985,2186],{"className":14986},[2323],[83,14988],{"className":14989,"style":2319},[2242],[83,14991,14993,14996,14999],{"className":14992},[2225],[83,14994],{"className":14995,"style":14779},[2229],[83,14997,14805],{"className":14998},[2234],[83,15000,1640],{"className":15001},[2234,2264],[83,15003,15005],{"className":15004},[2147],[83,15006,15008,15032],{"className":15007},[2151],[83,15009,15011],{"className":15010},[2155],[2157,15012,15013],{"xmlns":2159,"display":2160},[2162,15014,15015,15029],{},[2165,15016,15017,15023,15025,15027],{},[2202,15018,15019,15021],{"accent":2204},[2178,15020,3972],{},[2172,15022,8661],{},[2172,15024,229],{},[2182,15026,14805],{},[2178,15028,1640],{},[2214,15030,15031],{"encoding":2216},"\\hat{y} = 2000x",[83,15033,15035,15092],{"className":15034,"ariaHidden":2204},[2221],[83,15036,15038,15041,15083,15086,15089],{"className":15037},[2225],[83,15039],{"className":15040,"style":2257},[2229],[83,15042,15044],{"className":15043},[2234,2398],[83,15045,15047,15075],{"className":15046},[2273,2274],[83,15048,15050,15072],{"className":15049},[2278],[83,15051,15053,15061],{"className":15052,"style":2388},[2282],[83,15054,15055,15058],{"style":2410},[83,15056],{"className":15057,"style":2414},[2290],[83,15059,3972],{"className":15060,"style":6311},[2234,2264],[83,15062,15063,15066],{"style":2410},[83,15064],{"className":15065,"style":2414},[2290],[83,15067,15069],{"className":15068,"style":9858},[2426],[83,15070,8661],{"className":15071},[2234],[83,15073,2306],{"className":15074},[2305],[83,15076,15078],{"className":15077},[2278],[83,15079,15081],{"className":15080,"style":8875},[2282],[83,15082],{},[83,15084],{"className":15085,"style":2243},[2242],[83,15087,229],{"className":15088},[2247],[83,15090],{"className":15091,"style":2243},[2242],[83,15093,15095,15098,15101],{"className":15094},[2225],[83,15096],{"className":15097,"style":14779},[2229],[83,15099,14805],{"className":15100},[2234],[83,15102,1640],{"className":15103},[2234,2264],[12,15105,15106],{},"Ahora podemos hacer predicciones para nuevos valores de tamaño. Por ejemplo, para una casa de 120 m², el modelo predice un precio de:",[83,15108,15110],{"className":15109},[2147],[83,15111,15113,15150],{"className":15112},[2151],[83,15114,15116],{"className":15115},[2155],[2157,15117,15118],{"xmlns":2159,"display":2160},[2162,15119,15120,15147],{},[2165,15121,15122,15128,15130,15132,15134,15137,15139,15142,15144],{},[2202,15123,15124,15126],{"accent":2204},[2178,15125,3972],{},[2172,15127,8661],{},[2172,15129,229],{},[2182,15131,14805],{},[2172,15133,13760],{},[2182,15135,15136],{},"120",[2172,15138,229],{},[2182,15140,15141],{},"240",[2172,15143,256],{"separator":2204},[2182,15145,15146],{},"000",[2214,15148,15149],{"encoding":2216},"\\hat{y} = 2000 * 120 = 240,000",[83,15151,15153,15210,15228,15246],{"className":15152,"ariaHidden":2204},[2221],[83,15154,15156,15159,15201,15204,15207],{"className":15155},[2225],[83,15157],{"className":15158,"style":2257},[2229],[83,15160,15162],{"className":15161},[2234,2398],[83,15163,15165,15193],{"className":15164},[2273,2274],[83,15166,15168,15190],{"className":15167},[2278],[83,15169,15171,15179],{"className":15170,"style":2388},[2282],[83,15172,15173,15176],{"style":2410},[83,15174],{"className":15175,"style":2414},[2290],[83,15177,3972],{"className":15178,"style":6311},[2234,2264],[83,15180,15181,15184],{"style":2410},[83,15182],{"className":15183,"style":2414},[2290],[83,15185,15187],{"className":15186,"style":9858},[2426],[83,15188,8661],{"className":15189},[2234],[83,15191,2306],{"className":15192},[2305],[83,15194,15196],{"className":15195},[2278],[83,15197,15199],{"className":15198,"style":8875},[2282],[83,15200],{},[83,15202],{"className":15203,"style":2243},[2242],[83,15205,229],{"className":15206},[2247],[83,15208],{"className":15209,"style":2243},[2242],[83,15211,15213,15216,15219,15222,15225],{"className":15212},[2225],[83,15214],{"className":15215,"style":14779},[2229],[83,15217,14805],{"className":15218},[2234],[83,15220],{"className":15221,"style":2319},[2242],[83,15223,13760],{"className":15224},[2323],[83,15226],{"className":15227,"style":2319},[2242],[83,15229,15231,15234,15237,15240,15243],{"className":15230},[2225],[83,15232],{"className":15233,"style":14779},[2229],[83,15235,15136],{"className":15236},[2234],[83,15238],{"className":15239,"style":2243},[2242],[83,15241,229],{"className":15242},[2247],[83,15244],{"className":15245,"style":2243},[2242],[83,15247,15249,15253,15256,15259,15262],{"className":15248},[2225],[83,15250],{"className":15251,"style":15252},[2229],"height:0.8389em;vertical-align:-0.1944em;",[83,15254,15141],{"className":15255},[2234],[83,15257,256],{"className":15258},[6300],[83,15260],{"className":15261,"style":6304},[2242],[83,15263,15146],{"className":15264},[2234],[12,15266,15267,15268,15271],{},"Los cálculos nos han dado los mejores coeficientes que ",[40,15269,15270],{},"minimizan"," el error cuadrático medio (pero no que lo eliminan completamente). Para medir el error de nuestro modelo, podemos calcular el MSE utilizando la fórmula que mencionamos antes:",[83,15273,15275],{"className":15274},[2147],[83,15276,15278,15343],{"className":15277},[2151],[83,15279,15281],{"className":15280},[2155],[2157,15282,15283],{"xmlns":2159,"display":2160},[2162,15284,15285,15341],{},[2165,15286,15287,15289,15291,15293,15295,15301,15315,15317,15323,15325,15335],{},[2178,15288,9239],{},[2178,15290,9242],{},[2178,15292,9245],{},[2172,15294,229],{},[9249,15296,15297,15299],{},[2182,15298,1161],{},[2178,15300,313],{},[9256,15302,15303,15305,15313],{},[2172,15304,9260],{},[2165,15306,15307,15309,15311],{},[2178,15308,6578],{},[2172,15310,229],{},[2182,15312,1161],{},[2178,15314,313],{},[2172,15316,187],{"stretchy":6169},[2175,15318,15319,15321],{},[2178,15320,3972],{},[2178,15322,6578],{},[2172,15324,8650],{},[2202,15326,15327,15333],{"accent":2204},[2175,15328,15329,15331],{},[2178,15330,3972],{},[2178,15332,6578],{},[2172,15334,8661],{},[3702,15336,15337,15339],{},[2172,15338,534],{"stretchy":6169},[2182,15340,1149],{},[2214,15342,9299],{"encoding":2216},[83,15344,15346,15370,15560],{"className":15345,"ariaHidden":2204},[2221],[83,15347,15349,15352,15355,15358,15361,15364,15367],{"className":15348},[2225],[83,15350],{"className":15351,"style":2230},[2229],[83,15353,9239],{"className":15354,"style":9312},[2234,2264],[83,15356,9242],{"className":15357,"style":9316},[2234,2264],[83,15359,9245],{"className":15360,"style":9316},[2234,2264],[83,15362],{"className":15363,"style":2243},[2242],[83,15365,229],{"className":15366},[2247],[83,15368],{"className":15369,"style":2243},[2242],[83,15371,15373,15376,15438,15441,15508,15511,15551,15554,15557],{"className":15372},[2225],[83,15374],{"className":15375,"style":9335},[2229],[83,15377,15379,15382,15435],{"className":15378},[2234],[83,15380],{"className":15381},[6254,9342],[83,15383,15385],{"className":15384},[9249],[83,15386,15388,15427],{"className":15387},[2273,2274],[83,15389,15391,15424],{"className":15390},[2278],[83,15392,15394,15405,15413],{"className":15393,"style":9355},[2282],[83,15395,15396,15399],{"style":9358},[83,15397],{"className":15398,"style":2414},[2290],[83,15400,15402],{"className":15401},[2234],[83,15403,313],{"className":15404},[2234,2264],[83,15406,15407,15410],{"style":9370},[83,15408],{"className":15409,"style":2414},[2290],[83,15411],{"className":15412,"style":9378},[9377],[83,15414,15415,15418],{"style":9381},[83,15416],{"className":15417,"style":2414},[2290],[83,15419,15421],{"className":15420},[2234],[83,15422,1161],{"className":15423},[2234],[83,15425,2306],{"className":15426},[2305],[83,15428,15430],{"className":15429},[2278],[83,15431,15433],{"className":15432,"style":9400},[2282],[83,15434],{},[83,15436],{"className":15437},[6350,9342],[83,15439],{"className":15440,"style":6304},[2242],[83,15442,15444],{"className":15443},[9412,9413],[83,15445,15447,15500],{"className":15446},[2273,2274],[83,15448,15450,15497],{"className":15449},[2278],[83,15451,15453,15473,15483],{"className":15452,"style":9423},[2282],[83,15454,15455,15458],{"style":9426},[83,15456],{"className":15457,"style":9430},[2290],[83,15459,15461],{"className":15460},[2295,2296,2297,2298],[83,15462,15464,15467,15470],{"className":15463},[2234,2298],[83,15465,6578],{"className":15466},[2234,2264,2298],[83,15468,229],{"className":15469},[2247,2298],[83,15471,1161],{"className":15472},[2234,2298],[83,15474,15475,15478],{"style":9448},[83,15476],{"className":15477,"style":9430},[2290],[83,15479,15480],{},[83,15481,9260],{"className":15482},[9412,9457,9458],[83,15484,15485,15488],{"style":9461},[83,15486],{"className":15487,"style":9430},[2290],[83,15489,15491],{"className":15490},[2295,2296,2297,2298],[83,15492,15494],{"className":15493},[2234,2298],[83,15495,313],{"className":15496},[2234,2264,2298],[83,15498,2306],{"className":15499},[2305],[83,15501,15503],{"className":15502},[2278],[83,15504,15506],{"className":15505,"style":9483},[2282],[83,15507],{},[83,15509,187],{"className":15510},[6254],[83,15512,15514,15517],{"className":15513},[2234],[83,15515,3972],{"className":15516,"style":6311},[2234,2264],[83,15518,15520],{"className":15519},[2269],[83,15521,15523,15543],{"className":15522},[2273,2274],[83,15524,15526,15540],{"className":15525},[2278],[83,15527,15529],{"className":15528,"style":6610},[2282],[83,15530,15531,15534],{"style":6326},[83,15532],{"className":15533,"style":2291},[2290],[83,15535,15537],{"className":15536},[2295,2296,2297,2298],[83,15538,6578],{"className":15539},[2234,2264,2298],[83,15541,2306],{"className":15542},[2305],[83,15544,15546],{"className":15545},[2278],[83,15547,15549],{"className":15548,"style":2313},[2282],[83,15550],{},[83,15552],{"className":15553,"style":2319},[2242],[83,15555,8650],{"className":15556},[2323],[83,15558],{"className":15559,"style":2319},[2242],[83,15561,15563,15566,15645],{"className":15562},[2225],[83,15564],{"className":15565,"style":9544},[2229],[83,15567,15569],{"className":15568},[2234,2398],[83,15570,15572,15637],{"className":15571},[2273,2274],[83,15573,15575,15634],{"className":15574},[2278],[83,15576,15578,15623],{"className":15577,"style":2388},[2282],[83,15579,15580,15583],{"style":2410},[83,15581],{"className":15582,"style":2414},[2290],[83,15584,15586,15589],{"className":15585},[2234],[83,15587,3972],{"className":15588,"style":6311},[2234,2264],[83,15590,15592],{"className":15591},[2269],[83,15593,15595,15615],{"className":15594},[2273,2274],[83,15596,15598,15612],{"className":15597},[2278],[83,15599,15601],{"className":15600,"style":6610},[2282],[83,15602,15603,15606],{"style":6326},[83,15604],{"className":15605,"style":2291},[2290],[83,15607,15609],{"className":15608},[2295,2296,2297,2298],[83,15610,6578],{"className":15611},[2234,2264,2298],[83,15613,2306],{"className":15614},[2305],[83,15616,15618],{"className":15617},[2278],[83,15619,15621],{"className":15620,"style":2313},[2282],[83,15622],{},[83,15624,15625,15628],{"style":2410},[83,15626],{"className":15627,"style":2414},[2290],[83,15629,15631],{"className":15630,"style":2427},[2426],[83,15632,8661],{"className":15633},[2234],[83,15635,2306],{"className":15636},[2305],[83,15638,15640],{"className":15639},[2278],[83,15641,15643],{"className":15642,"style":8875},[2282],[83,15644],{},[83,15646,15648,15651],{"className":15647},[6350],[83,15649,534],{"className":15650},[6350],[83,15652,15654],{"className":15653},[2269],[83,15655,15657],{"className":15656},[2273],[83,15658,15660],{"className":15659},[2278],[83,15661,15663],{"className":15662,"style":9642},[2282],[83,15664,15665,15668],{"style":9645},[83,15666],{"className":15667,"style":2291},[2290],[83,15669,15671],{"className":15670},[2295,2296,2297,2298],[83,15672,1149],{"className":15673},[2234,2298],[12,15675,7598],{},[1359,15677,15678,15708,15780],{},[1362,15679,15680,13446],{},[83,15681,15683,15696],{"className":15682},[2151],[83,15684,15686],{"className":15685},[2155],[2157,15687,15688],{"xmlns":2159},[2162,15689,15690,15694],{},[2165,15691,15692],{},[2178,15693,313],{},[2214,15695,313],{"encoding":2216},[83,15697,15699],{"className":15698,"ariaHidden":2204},[2221],[83,15700,15702,15705],{"className":15701},[2225],[83,15703],{"className":15704,"style":7592},[2229],[83,15706,313],{"className":15707},[2234,2264],[1362,15709,15710,15779],{},[83,15711,15713,15730],{"className":15712},[2151],[83,15714,15716],{"className":15715},[2155],[2157,15717,15718],{"xmlns":2159},[2162,15719,15720,15728],{},[2165,15721,15722],{},[2175,15723,15724,15726],{},[2178,15725,3972],{},[2178,15727,6578],{},[2214,15729,6654],{"encoding":2216},[83,15731,15733],{"className":15732,"ariaHidden":2204},[2221],[83,15734,15736,15739],{"className":15735},[2225],[83,15737],{"className":15738,"style":6664},[2229],[83,15740,15742,15745],{"className":15741},[2234],[83,15743,3972],{"className":15744,"style":6311},[2234,2264],[83,15746,15748],{"className":15747},[2269],[83,15749,15751,15771],{"className":15750},[2273,2274],[83,15752,15754,15768],{"className":15753},[2278],[83,15755,15757],{"className":15756,"style":6610},[2282],[83,15758,15759,15762],{"style":6326},[83,15760],{"className":15761,"style":2291},[2290],[83,15763,15765],{"className":15764},[2295,2296,2297,2298],[83,15766,6578],{"className":15767},[2234,2264,2298],[83,15769,2306],{"className":15770},[2305],[83,15772,15774],{"className":15773},[2278],[83,15775,15777],{"className":15776,"style":2313},[2282],[83,15778],{}," son los valores reales de precio para cada ejemplo.",[1362,15781,15782,15894],{},[83,15783,15785,15806],{"className":15784},[2151],[83,15786,15788],{"className":15787},[2155],[2157,15789,15790],{"xmlns":2159},[2162,15791,15792,15804],{},[2165,15793,15794],{},[2175,15795,15796,15802],{},[2202,15797,15798,15800],{"accent":2204},[2178,15799,3972],{},[2172,15801,8661],{},[2178,15803,6578],{},[2214,15805,9817],{"encoding":2216},[83,15807,15809],{"className":15808,"ariaHidden":2204},[2221],[83,15810,15812,15815],{"className":15811},[2225],[83,15813],{"className":15814,"style":2257},[2229],[83,15816,15818,15860],{"className":15817},[2234],[83,15819,15821],{"className":15820},[2234,2398],[83,15822,15824,15852],{"className":15823},[2273,2274],[83,15825,15827,15849],{"className":15826},[2278],[83,15828,15830,15838],{"className":15829,"style":2388},[2282],[83,15831,15832,15835],{"style":2410},[83,15833],{"className":15834,"style":2414},[2290],[83,15836,3972],{"className":15837,"style":6311},[2234,2264],[83,15839,15840,15843],{"style":2410},[83,15841],{"className":15842,"style":2414},[2290],[83,15844,15846],{"className":15845,"style":9858},[2426],[83,15847,8661],{"className":15848},[2234],[83,15850,2306],{"className":15851},[2305],[83,15853,15855],{"className":15854},[2278],[83,15856,15858],{"className":15857,"style":8875},[2282],[83,15859],{},[83,15861,15863],{"className":15862},[2269],[83,15864,15866,15886],{"className":15865},[2273,2274],[83,15867,15869,15883],{"className":15868},[2278],[83,15870,15872],{"className":15871,"style":6610},[2282],[83,15873,15874,15877],{"style":6326},[83,15875],{"className":15876,"style":2291},[2290],[83,15878,15880],{"className":15879},[2295,2296,2297,2298],[83,15881,6578],{"className":15882},[2234,2264,2298],[83,15884,2306],{"className":15885},[2305],[83,15887,15889],{"className":15888},[2278],[83,15890,15892],{"className":15891,"style":2313},[2282],[83,15893],{}," son las predicciones del modelo para cada ejemplo, que se calculan usando el modelo de regresión lineal.",[1406,15896,15897],{},[1362,15898,15899],{},"Calculamos las predicciones para cada ejemplo:",[1359,15901,15902,16097,16293],{},[1362,15903,15904,15905],{},"Para 50 m²: ",[83,15906,15908,15946],{"className":15907},[2151],[83,15909,15911],{"className":15910},[2155],[2157,15912,15913],{"xmlns":2159},[2162,15914,15915,15943],{},[2165,15916,15917,15927,15929,15931,15933,15935,15937,15939,15941],{},[2202,15918,15919,15925],{"accent":2204},[2175,15920,15921,15923],{},[2178,15922,3972],{},[2182,15924,1161],{},[2172,15926,8661],{},[2172,15928,229],{},[2182,15930,14805],{},[2172,15932,13760],{},[2182,15934,12005],{},[2172,15936,229],{},[2182,15938,12013],{},[2172,15940,256],{"separator":2204},[2182,15942,15146],{},[2214,15944,15945],{"encoding":2216},"\\hat{y_1} = 2000 * 50 = 100,000",[83,15947,15949,16043,16061,16079],{"className":15948,"ariaHidden":2204},[2221],[83,15950,15952,15955,16034,16037,16040],{"className":15951},[2225],[83,15953],{"className":15954,"style":2257},[2229],[83,15956,15958],{"className":15957},[2234,2398],[83,15959,15961,16026],{"className":15960},[2273,2274],[83,15962,15964,16023],{"className":15963},[2278],[83,15965,15967,16012],{"className":15966,"style":2388},[2282],[83,15968,15969,15972],{"style":2410},[83,15970],{"className":15971,"style":2414},[2290],[83,15973,15975,15978],{"className":15974},[2234],[83,15976,3972],{"className":15977,"style":6311},[2234,2264],[83,15979,15981],{"className":15980},[2269],[83,15982,15984,16004],{"className":15983},[2273,2274],[83,15985,15987,16001],{"className":15986},[2278],[83,15988,15990],{"className":15989,"style":2283},[2282],[83,15991,15992,15995],{"style":6326},[83,15993],{"className":15994,"style":2291},[2290],[83,15996,15998],{"className":15997},[2295,2296,2297,2298],[83,15999,1161],{"className":16000},[2234,2298],[83,16002,2306],{"className":16003},[2305],[83,16005,16007],{"className":16006},[2278],[83,16008,16010],{"className":16009,"style":2313},[2282],[83,16011],{},[83,16013,16014,16017],{"style":2410},[83,16015],{"className":16016,"style":2414},[2290],[83,16018,16020],{"className":16019,"style":2427},[2426],[83,16021,8661],{"className":16022},[2234],[83,16024,2306],{"className":16025},[2305],[83,16027,16029],{"className":16028},[2278],[83,16030,16032],{"className":16031,"style":8875},[2282],[83,16033],{},[83,16035],{"className":16036,"style":2243},[2242],[83,16038,229],{"className":16039},[2247],[83,16041],{"className":16042,"style":2243},[2242],[83,16044,16046,16049,16052,16055,16058],{"className":16045},[2225],[83,16047],{"className":16048,"style":14779},[2229],[83,16050,14805],{"className":16051},[2234],[83,16053],{"className":16054,"style":2319},[2242],[83,16056,13760],{"className":16057},[2323],[83,16059],{"className":16060,"style":2319},[2242],[83,16062,16064,16067,16070,16073,16076],{"className":16063},[2225],[83,16065],{"className":16066,"style":14779},[2229],[83,16068,12005],{"className":16069},[2234],[83,16071],{"className":16072,"style":2243},[2242],[83,16074,229],{"className":16075},[2247],[83,16077],{"className":16078,"style":2243},[2242],[83,16080,16082,16085,16088,16091,16094],{"className":16081},[2225],[83,16083],{"className":16084,"style":15252},[2229],[83,16086,12013],{"className":16087},[2234],[83,16089,256],{"className":16090},[6300],[83,16092],{"className":16093,"style":6304},[2242],[83,16095,15146],{"className":16096},[2234],[1362,16098,16099,16100],{},"Para 100 m²: ",[83,16101,16103,16142],{"className":16102},[2151],[83,16104,16106],{"className":16105},[2155],[2157,16107,16108],{"xmlns":2159},[2162,16109,16110,16139],{},[2165,16111,16112,16122,16124,16126,16128,16130,16132,16135,16137],{},[2202,16113,16114,16120],{"accent":2204},[2175,16115,16116,16118],{},[2178,16117,3972],{},[2182,16119,1149],{},[2172,16121,8661],{},[2172,16123,229],{},[2182,16125,14805],{},[2172,16127,13760],{},[2182,16129,12013],{},[2172,16131,229],{},[2182,16133,16134],{},"200",[2172,16136,256],{"separator":2204},[2182,16138,15146],{},[2214,16140,16141],{"encoding":2216},"\\hat{y_2} = 2000 * 100 = 200,000",[83,16143,16145,16239,16257,16275],{"className":16144,"ariaHidden":2204},[2221],[83,16146,16148,16151,16230,16233,16236],{"className":16147},[2225],[83,16149],{"className":16150,"style":2257},[2229],[83,16152,16154],{"className":16153},[2234,2398],[83,16155,16157,16222],{"className":16156},[2273,2274],[83,16158,16160,16219],{"className":16159},[2278],[83,16161,16163,16208],{"className":16162,"style":2388},[2282],[83,16164,16165,16168],{"style":2410},[83,16166],{"className":16167,"style":2414},[2290],[83,16169,16171,16174],{"className":16170},[2234],[83,16172,3972],{"className":16173,"style":6311},[2234,2264],[83,16175,16177],{"className":16176},[2269],[83,16178,16180,16200],{"className":16179},[2273,2274],[83,16181,16183,16197],{"className":16182},[2278],[83,16184,16186],{"className":16185,"style":2283},[2282],[83,16187,16188,16191],{"style":6326},[83,16189],{"className":16190,"style":2291},[2290],[83,16192,16194],{"className":16193},[2295,2296,2297,2298],[83,16195,1149],{"className":16196},[2234,2298],[83,16198,2306],{"className":16199},[2305],[83,16201,16203],{"className":16202},[2278],[83,16204,16206],{"className":16205,"style":2313},[2282],[83,16207],{},[83,16209,16210,16213],{"style":2410},[83,16211],{"className":16212,"style":2414},[2290],[83,16214,16216],{"className":16215,"style":2427},[2426],[83,16217,8661],{"className":16218},[2234],[83,16220,2306],{"className":16221},[2305],[83,16223,16225],{"className":16224},[2278],[83,16226,16228],{"className":16227,"style":8875},[2282],[83,16229],{},[83,16231],{"className":16232,"style":2243},[2242],[83,16234,229],{"className":16235},[2247],[83,16237],{"className":16238,"style":2243},[2242],[83,16240,16242,16245,16248,16251,16254],{"className":16241},[2225],[83,16243],{"className":16244,"style":14779},[2229],[83,16246,14805],{"className":16247},[2234],[83,16249],{"className":16250,"style":2319},[2242],[83,16252,13760],{"className":16253},[2323],[83,16255],{"className":16256,"style":2319},[2242],[83,16258,16260,16263,16266,16269,16272],{"className":16259},[2225],[83,16261],{"className":16262,"style":14779},[2229],[83,16264,12013],{"className":16265},[2234],[83,16267],{"className":16268,"style":2243},[2242],[83,16270,229],{"className":16271},[2247],[83,16273],{"className":16274,"style":2243},[2242],[83,16276,16278,16281,16284,16287,16290],{"className":16277},[2225],[83,16279],{"className":16280,"style":15252},[2229],[83,16282,16134],{"className":16283},[2234],[83,16285,256],{"className":16286},[6300],[83,16288],{"className":16289,"style":6304},[2242],[83,16291,15146],{"className":16292},[2234],[1362,16294,16295,16296],{},"Para 150 m²: ",[83,16297,16299,16338],{"className":16298},[2151],[83,16300,16302],{"className":16301},[2155],[2157,16303,16304],{"xmlns":2159},[2162,16305,16306,16335],{},[2165,16307,16308,16318,16320,16322,16324,16326,16328,16331,16333],{},[2202,16309,16310,16316],{"accent":2204},[2175,16311,16312,16314],{},[2178,16313,3972],{},[2182,16315,1137],{},[2172,16317,8661],{},[2172,16319,229],{},[2182,16321,14805],{},[2172,16323,13760],{},[2182,16325,12021],{},[2172,16327,229],{},[2182,16329,16330],{},"300",[2172,16332,256],{"separator":2204},[2182,16334,15146],{},[2214,16336,16337],{"encoding":2216},"\\hat{y_3} = 2000 * 150 = 300,000",[83,16339,16341,16435,16453,16471],{"className":16340,"ariaHidden":2204},[2221],[83,16342,16344,16347,16426,16429,16432],{"className":16343},[2225],[83,16345],{"className":16346,"style":2257},[2229],[83,16348,16350],{"className":16349},[2234,2398],[83,16351,16353,16418],{"className":16352},[2273,2274],[83,16354,16356,16415],{"className":16355},[2278],[83,16357,16359,16404],{"className":16358,"style":2388},[2282],[83,16360,16361,16364],{"style":2410},[83,16362],{"className":16363,"style":2414},[2290],[83,16365,16367,16370],{"className":16366},[2234],[83,16368,3972],{"className":16369,"style":6311},[2234,2264],[83,16371,16373],{"className":16372},[2269],[83,16374,16376,16396],{"className":16375},[2273,2274],[83,16377,16379,16393],{"className":16378},[2278],[83,16380,16382],{"className":16381,"style":2283},[2282],[83,16383,16384,16387],{"style":6326},[83,16385],{"className":16386,"style":2291},[2290],[83,16388,16390],{"className":16389},[2295,2296,2297,2298],[83,16391,1137],{"className":16392},[2234,2298],[83,16394,2306],{"className":16395},[2305],[83,16397,16399],{"className":16398},[2278],[83,16400,16402],{"className":16401,"style":2313},[2282],[83,16403],{},[83,16405,16406,16409],{"style":2410},[83,16407],{"className":16408,"style":2414},[2290],[83,16410,16412],{"className":16411,"style":2427},[2426],[83,16413,8661],{"className":16414},[2234],[83,16416,2306],{"className":16417},[2305],[83,16419,16421],{"className":16420},[2278],[83,16422,16424],{"className":16423,"style":8875},[2282],[83,16425],{},[83,16427],{"className":16428,"style":2243},[2242],[83,16430,229],{"className":16431},[2247],[83,16433],{"className":16434,"style":2243},[2242],[83,16436,16438,16441,16444,16447,16450],{"className":16437},[2225],[83,16439],{"className":16440,"style":14779},[2229],[83,16442,14805],{"className":16443},[2234],[83,16445],{"className":16446,"style":2319},[2242],[83,16448,13760],{"className":16449},[2323],[83,16451],{"className":16452,"style":2319},[2242],[83,16454,16456,16459,16462,16465,16468],{"className":16455},[2225],[83,16457],{"className":16458,"style":14779},[2229],[83,16460,12021],{"className":16461},[2234],[83,16463],{"className":16464,"style":2243},[2242],[83,16466,229],{"className":16467},[2247],[83,16469],{"className":16470,"style":2243},[2242],[83,16472,16474,16477,16480,16483,16486],{"className":16473},[2225],[83,16475],{"className":16476,"style":15252},[2229],[83,16478,16330],{"className":16479},[2234],[83,16481,256],{"className":16482},[6300],[83,16484],{"className":16485,"style":6304},[2242],[83,16487,15146],{"className":16488},[2234],[1406,16490,16491],{"start":103},[1362,16492,16493],{},"Calculamos los errores para cada ejemplo:",[83,16495,16497],{"className":16496},[2147],[83,16498,16500,16539],{"className":16499},[2151],[83,16501,16503],{"className":16502},[2155],[2157,16504,16505],{"xmlns":2159,"display":2160},[2162,16506,16507,16536],{},[2165,16508,16509,16516,16518,16524,16526],{},[2175,16510,16511,16514],{},[2178,16512,16513],{},"e",[2178,16515,6578],{},[2172,16517,229],{},[2175,16519,16520,16522],{},[2178,16521,3972],{},[2178,16523,6578],{},[2172,16525,8650],{},[2202,16527,16528,16534],{"accent":2204},[2175,16529,16530,16532],{},[2178,16531,3972],{},[2178,16533,6578],{},[2172,16535,8661],{},[2214,16537,16538],{"encoding":2216},"e_i = y_i - \\hat{y_i}",[83,16540,16542,16597,16652],{"className":16541,"ariaHidden":2204},[2221],[83,16543,16545,16548,16588,16591,16594],{"className":16544},[2225],[83,16546],{"className":16547,"style":6591},[2229],[83,16549,16551,16554],{"className":16550},[2234],[83,16552,16513],{"className":16553},[2234,2264],[83,16555,16557],{"className":16556},[2269],[83,16558,16560,16580],{"className":16559},[2273,2274],[83,16561,16563,16577],{"className":16562},[2278],[83,16564,16566],{"className":16565,"style":6610},[2282],[83,16567,16568,16571],{"style":6276},[83,16569],{"className":16570,"style":2291},[2290],[83,16572,16574],{"className":16573},[2295,2296,2297,2298],[83,16575,6578],{"className":16576},[2234,2264,2298],[83,16578,2306],{"className":16579},[2305],[83,16581,16583],{"className":16582},[2278],[83,16584,16586],{"className":16585,"style":2313},[2282],[83,16587],{},[83,16589],{"className":16590,"style":2243},[2242],[83,16592,229],{"className":16593},[2247],[83,16595],{"className":16596,"style":2243},[2242],[83,16598,16600,16603,16643,16646,16649],{"className":16599},[2225],[83,16601],{"className":16602,"style":8737},[2229],[83,16604,16606,16609],{"className":16605},[2234],[83,16607,3972],{"className":16608,"style":6311},[2234,2264],[83,16610,16612],{"className":16611},[2269],[83,16613,16615,16635],{"className":16614},[2273,2274],[83,16616,16618,16632],{"className":16617},[2278],[83,16619,16621],{"className":16620,"style":6610},[2282],[83,16622,16623,16626],{"style":6326},[83,16624],{"className":16625,"style":2291},[2290],[83,16627,16629],{"className":16628},[2295,2296,2297,2298],[83,16630,6578],{"className":16631},[2234,2264,2298],[83,16633,2306],{"className":16634},[2305],[83,16636,16638],{"className":16637},[2278],[83,16639,16641],{"className":16640,"style":2313},[2282],[83,16642],{},[83,16644],{"className":16645,"style":2319},[2242],[83,16647,8650],{"className":16648},[2323],[83,16650],{"className":16651,"style":2319},[2242],[83,16653,16655,16658],{"className":16654},[2225],[83,16656],{"className":16657,"style":2257},[2229],[83,16659,16661],{"className":16660},[2234,2398],[83,16662,16664,16729],{"className":16663},[2273,2274],[83,16665,16667,16726],{"className":16666},[2278],[83,16668,16670,16715],{"className":16669,"style":2388},[2282],[83,16671,16672,16675],{"style":2410},[83,16673],{"className":16674,"style":2414},[2290],[83,16676,16678,16681],{"className":16677},[2234],[83,16679,3972],{"className":16680,"style":6311},[2234,2264],[83,16682,16684],{"className":16683},[2269],[83,16685,16687,16707],{"className":16686},[2273,2274],[83,16688,16690,16704],{"className":16689},[2278],[83,16691,16693],{"className":16692,"style":6610},[2282],[83,16694,16695,16698],{"style":6326},[83,16696],{"className":16697,"style":2291},[2290],[83,16699,16701],{"className":16700},[2295,2296,2297,2298],[83,16702,6578],{"className":16703},[2234,2264,2298],[83,16705,2306],{"className":16706},[2305],[83,16708,16710],{"className":16709},[2278],[83,16711,16713],{"className":16712,"style":2313},[2282],[83,16714],{},[83,16716,16717,16720],{"style":2410},[83,16718],{"className":16719,"style":2414},[2290],[83,16721,16723],{"className":16722,"style":2427},[2426],[83,16724,8661],{"className":16725},[2234],[83,16727,2306],{"className":16728},[2305],[83,16730,16732],{"className":16731},[2278],[83,16733,16735],{"className":16734,"style":8875},[2282],[83,16736],{},[1359,16738,16739,16878,17017],{},[1362,16740,16741,16742],{},"Error para 50 m²: ",[83,16743,16745,16775],{"className":16744},[2151],[83,16746,16748],{"className":16747},[2155],[2157,16749,16750],{"xmlns":2159},[2162,16751,16752,16772],{},[2165,16753,16754,16760,16762,16764,16766,16768,16770],{},[2175,16755,16756,16758],{},[2178,16757,16513],{},[2182,16759,1161],{},[2172,16761,229],{},[2182,16763,13763],{},[2172,16765,8650],{},[2182,16767,13763],{},[2172,16769,229],{},[2182,16771,411],{},[2214,16773,16774],{"encoding":2216},"e_1 = 100000 - 100000 = 0",[83,16776,16778,16833,16851,16869],{"className":16777,"ariaHidden":2204},[2221],[83,16779,16781,16784,16824,16827,16830],{"className":16780},[2225],[83,16782],{"className":16783,"style":6591},[2229],[83,16785,16787,16790],{"className":16786},[2234],[83,16788,16513],{"className":16789},[2234,2264],[83,16791,16793],{"className":16792},[2269],[83,16794,16796,16816],{"className":16795},[2273,2274],[83,16797,16799,16813],{"className":16798},[2278],[83,16800,16802],{"className":16801,"style":2283},[2282],[83,16803,16804,16807],{"style":6276},[83,16805],{"className":16806,"style":2291},[2290],[83,16808,16810],{"className":16809},[2295,2296,2297,2298],[83,16811,1161],{"className":16812},[2234,2298],[83,16814,2306],{"className":16815},[2305],[83,16817,16819],{"className":16818},[2278],[83,16820,16822],{"className":16821,"style":2313},[2282],[83,16823],{},[83,16825],{"className":16826,"style":2243},[2242],[83,16828,229],{"className":16829},[2247],[83,16831],{"className":16832,"style":2243},[2242],[83,16834,16836,16839,16842,16845,16848],{"className":16835},[2225],[83,16837],{"className":16838,"style":14977},[2229],[83,16840,13763],{"className":16841},[2234],[83,16843],{"className":16844,"style":2319},[2242],[83,16846,8650],{"className":16847},[2323],[83,16849],{"className":16850,"style":2319},[2242],[83,16852,16854,16857,16860,16863,16866],{"className":16853},[2225],[83,16855],{"className":16856,"style":14779},[2229],[83,16858,13763],{"className":16859},[2234],[83,16861],{"className":16862,"style":2243},[2242],[83,16864,229],{"className":16865},[2247],[83,16867],{"className":16868,"style":2243},[2242],[83,16870,16872,16875],{"className":16871},[2225],[83,16873],{"className":16874,"style":14779},[2229],[83,16876,411],{"className":16877},[2234],[1362,16879,16880,16881],{},"Error para 100 m²: ",[83,16882,16884,16914],{"className":16883},[2151],[83,16885,16887],{"className":16886},[2155],[2157,16888,16889],{"xmlns":2159},[2162,16890,16891,16911],{},[2165,16892,16893,16899,16901,16903,16905,16907,16909],{},[2175,16894,16895,16897],{},[2178,16896,16513],{},[2182,16898,1149],{},[2172,16900,229],{},[2182,16902,13772],{},[2172,16904,8650],{},[2182,16906,13772],{},[2172,16908,229],{},[2182,16910,411],{},[2214,16912,16913],{"encoding":2216},"e_2 = 200000 - 200000 = 0",[83,16915,16917,16972,16990,17008],{"className":16916,"ariaHidden":2204},[2221],[83,16918,16920,16923,16963,16966,16969],{"className":16919},[2225],[83,16921],{"className":16922,"style":6591},[2229],[83,16924,16926,16929],{"className":16925},[2234],[83,16927,16513],{"className":16928},[2234,2264],[83,16930,16932],{"className":16931},[2269],[83,16933,16935,16955],{"className":16934},[2273,2274],[83,16936,16938,16952],{"className":16937},[2278],[83,16939,16941],{"className":16940,"style":2283},[2282],[83,16942,16943,16946],{"style":6276},[83,16944],{"className":16945,"style":2291},[2290],[83,16947,16949],{"className":16948},[2295,2296,2297,2298],[83,16950,1149],{"className":16951},[2234,2298],[83,16953,2306],{"className":16954},[2305],[83,16956,16958],{"className":16957},[2278],[83,16959,16961],{"className":16960,"style":2313},[2282],[83,16962],{},[83,16964],{"className":16965,"style":2243},[2242],[83,16967,229],{"className":16968},[2247],[83,16970],{"className":16971,"style":2243},[2242],[83,16973,16975,16978,16981,16984,16987],{"className":16974},[2225],[83,16976],{"className":16977,"style":14977},[2229],[83,16979,13772],{"className":16980},[2234],[83,16982],{"className":16983,"style":2319},[2242],[83,16985,8650],{"className":16986},[2323],[83,16988],{"className":16989,"style":2319},[2242],[83,16991,16993,16996,16999,17002,17005],{"className":16992},[2225],[83,16994],{"className":16995,"style":14779},[2229],[83,16997,13772],{"className":16998},[2234],[83,17000],{"className":17001,"style":2243},[2242],[83,17003,229],{"className":17004},[2247],[83,17006],{"className":17007,"style":2243},[2242],[83,17009,17011,17014],{"className":17010},[2225],[83,17012],{"className":17013,"style":14779},[2229],[83,17015,411],{"className":17016},[2234],[1362,17018,17019,17020],{},"Error para 150 m²: ",[83,17021,17023,17053],{"className":17022},[2151],[83,17024,17026],{"className":17025},[2155],[2157,17027,17028],{"xmlns":2159},[2162,17029,17030,17050],{},[2165,17031,17032,17038,17040,17042,17044,17046,17048],{},[2175,17033,17034,17036],{},[2178,17035,16513],{},[2182,17037,1137],{},[2172,17039,229],{},[2182,17041,13781],{},[2172,17043,8650],{},[2182,17045,13781],{},[2172,17047,229],{},[2182,17049,411],{},[2214,17051,17052],{"encoding":2216},"e_3 = 300000 - 300000 = 0",[83,17054,17056,17111,17129,17147],{"className":17055,"ariaHidden":2204},[2221],[83,17057,17059,17062,17102,17105,17108],{"className":17058},[2225],[83,17060],{"className":17061,"style":6591},[2229],[83,17063,17065,17068],{"className":17064},[2234],[83,17066,16513],{"className":17067},[2234,2264],[83,17069,17071],{"className":17070},[2269],[83,17072,17074,17094],{"className":17073},[2273,2274],[83,17075,17077,17091],{"className":17076},[2278],[83,17078,17080],{"className":17079,"style":2283},[2282],[83,17081,17082,17085],{"style":6276},[83,17083],{"className":17084,"style":2291},[2290],[83,17086,17088],{"className":17087},[2295,2296,2297,2298],[83,17089,1137],{"className":17090},[2234,2298],[83,17092,2306],{"className":17093},[2305],[83,17095,17097],{"className":17096},[2278],[83,17098,17100],{"className":17099,"style":2313},[2282],[83,17101],{},[83,17103],{"className":17104,"style":2243},[2242],[83,17106,229],{"className":17107},[2247],[83,17109],{"className":17110,"style":2243},[2242],[83,17112,17114,17117,17120,17123,17126],{"className":17113},[2225],[83,17115],{"className":17116,"style":14977},[2229],[83,17118,13781],{"className":17119},[2234],[83,17121],{"className":17122,"style":2319},[2242],[83,17124,8650],{"className":17125},[2323],[83,17127],{"className":17128,"style":2319},[2242],[83,17130,17132,17135,17138,17141,17144],{"className":17131},[2225],[83,17133],{"className":17134,"style":14779},[2229],[83,17136,13781],{"className":17137},[2234],[83,17139],{"className":17140,"style":2243},[2242],[83,17142,229],{"className":17143},[2247],[83,17145],{"className":17146,"style":2243},[2242],[83,17148,17150,17153],{"className":17149},[2225],[83,17151],{"className":17152,"style":14779},[2229],[83,17154,411],{"className":17155},[2234],[1406,17157,17158],{"start":116},[1362,17159,17160],{},"Elevamos al cuadrado y promediamos para obtener el MSE:",[83,17162,17164],{"className":17163},[2147],[83,17165,17167,17223],{"className":17166},[2151],[83,17168,17170],{"className":17169},[2155],[2157,17171,17172],{"xmlns":2159,"display":2160},[2162,17173,17174,17220],{},[2165,17175,17176,17178,17180,17182,17184,17190,17192,17198,17200,17206,17208,17214,17216,17218],{},[2178,17177,9239],{},[2178,17179,9242],{},[2178,17181,9245],{},[2172,17183,229],{},[9249,17185,17186,17188],{},[2182,17187,1161],{},[2182,17189,1137],{},[2172,17191,187],{"stretchy":6169},[3702,17193,17194,17196],{},[2182,17195,411],{},[2182,17197,1149],{},[2172,17199,2186],{},[3702,17201,17202,17204],{},[2182,17203,411],{},[2182,17205,1149],{},[2172,17207,2186],{},[3702,17209,17210,17212],{},[2182,17211,411],{},[2182,17213,1149],{},[2172,17215,534],{"stretchy":6169},[2172,17217,229],{},[2182,17219,411],{},[2214,17221,17222],{"encoding":2216},"MSE = \\frac{1}{3} (0^2 + 0^2 + 0^2) = 0",[83,17224,17226,17250,17359,17404,17451],{"className":17225,"ariaHidden":2204},[2221],[83,17227,17229,17232,17235,17238,17241,17244,17247],{"className":17228},[2225],[83,17230],{"className":17231,"style":2230},[2229],[83,17233,9239],{"className":17234,"style":9312},[2234,2264],[83,17236,9242],{"className":17237,"style":9316},[2234,2264],[83,17239,9245],{"className":17240,"style":9316},[2234,2264],[83,17242],{"className":17243,"style":2243},[2242],[83,17245,229],{"className":17246},[2247],[83,17248],{"className":17249,"style":2243},[2242],[83,17251,17253,17256,17318,17321,17350,17353,17356],{"className":17252},[2225],[83,17254],{"className":17255,"style":14459},[2229],[83,17257,17259,17262,17315],{"className":17258},[2234],[83,17260],{"className":17261},[6254,9342],[83,17263,17265],{"className":17264},[9249],[83,17266,17268,17307],{"className":17267},[2273,2274],[83,17269,17271,17304],{"className":17270},[2278],[83,17272,17274,17285,17293],{"className":17273,"style":9355},[2282],[83,17275,17276,17279],{"style":9358},[83,17277],{"className":17278,"style":2414},[2290],[83,17280,17282],{"className":17281},[2234],[83,17283,1137],{"className":17284},[2234],[83,17286,17287,17290],{"style":9370},[83,17288],{"className":17289,"style":2414},[2290],[83,17291],{"className":17292,"style":9378},[9377],[83,17294,17295,17298],{"style":9381},[83,17296],{"className":17297,"style":2414},[2290],[83,17299,17301],{"className":17300},[2234],[83,17302,1161],{"className":17303},[2234],[83,17305,2306],{"className":17306},[2305],[83,17308,17310],{"className":17309},[2278],[83,17311,17313],{"className":17312,"style":9400},[2282],[83,17314],{},[83,17316],{"className":17317},[6350,9342],[83,17319,187],{"className":17320},[6254],[83,17322,17324,17327],{"className":17323},[2234],[83,17325,411],{"className":17326},[2234],[83,17328,17330],{"className":17329},[2269],[83,17331,17333],{"className":17332},[2273],[83,17334,17336],{"className":17335},[2278],[83,17337,17339],{"className":17338,"style":9642},[2282],[83,17340,17341,17344],{"style":9645},[83,17342],{"className":17343,"style":2291},[2290],[83,17345,17347],{"className":17346},[2295,2296,2297,2298],[83,17348,1149],{"className":17349},[2234,2298],[83,17351],{"className":17352,"style":2319},[2242],[83,17354,2186],{"className":17355},[2323],[83,17357],{"className":17358,"style":2319},[2242],[83,17360,17362,17366,17395,17398,17401],{"className":17361},[2225],[83,17363],{"className":17364,"style":17365},[2229],"height:0.9474em;vertical-align:-0.0833em;",[83,17367,17369,17372],{"className":17368},[2234],[83,17370,411],{"className":17371},[2234],[83,17373,17375],{"className":17374},[2269],[83,17376,17378],{"className":17377},[2273],[83,17379,17381],{"className":17380},[2278],[83,17382,17384],{"className":17383,"style":9642},[2282],[83,17385,17386,17389],{"style":9645},[83,17387],{"className":17388,"style":2291},[2290],[83,17390,17392],{"className":17391},[2295,2296,2297,2298],[83,17393,1149],{"className":17394},[2234,2298],[83,17396],{"className":17397,"style":2319},[2242],[83,17399,2186],{"className":17400},[2323],[83,17402],{"className":17403,"style":2319},[2242],[83,17405,17407,17410,17439,17442,17445,17448],{"className":17406},[2225],[83,17408],{"className":17409,"style":9544},[2229],[83,17411,17413,17416],{"className":17412},[2234],[83,17414,411],{"className":17415},[2234],[83,17417,17419],{"className":17418},[2269],[83,17420,17422],{"className":17421},[2273],[83,17423,17425],{"className":17424},[2278],[83,17426,17428],{"className":17427,"style":9642},[2282],[83,17429,17430,17433],{"style":9645},[83,17431],{"className":17432,"style":2291},[2290],[83,17434,17436],{"className":17435},[2295,2296,2297,2298],[83,17437,1149],{"className":17438},[2234,2298],[83,17440,534],{"className":17441},[6350],[83,17443],{"className":17444,"style":2243},[2242],[83,17446,229],{"className":17447},[2247],[83,17449],{"className":17450,"style":2243},[2242],[83,17452,17454,17457],{"className":17453},[2225],[83,17455],{"className":17456,"style":14779},[2229],[83,17458,411],{"className":17459},[2234],[12,17461,17462,17463,17466,17467,17495],{},"Para este caso un MSE de 0 nos indica que el modelo predice perfectamente los valores reales para ",[40,17464,17465],{},"este conjunto de datos de entrenamiento",". Por supuesto que en la práctica los datos reales contendrán ruido y serán aún mayores, con mas variabilidad, por lo que el epsilon ",[83,17468,17470,17483],{"className":17469},[2151],[83,17471,17473],{"className":17472},[2155],[2157,17474,17475],{"xmlns":2159},[2162,17476,17477,17481],{},[2165,17478,17479],{},[2178,17480,7200],{},[2214,17482,8178],{"encoding":2216},[83,17484,17486],{"className":17485,"ariaHidden":2204},[2221],[83,17487,17489,17492],{"className":17488},[2225],[83,17490],{"className":17491,"style":7592},[2229],[83,17493,7200],{"className":17494},[2234,2264]," no será cero.",[12,17497,17498,17499],{},"Para explorar más con la regresión puedes usar este Colab de Google que contiene un ejemplo completo de regresión lineal con Python: ",[19,17500,17506],{"href":17501,"target":17502,"rel":17503},"https:\u002F\u002Fcolab.research.google.com\u002Fdrive\u002F1yi8-fVw2Ak7pqYOzZsiT7NO_zccZrQir?usp=sharing","_blank",[17504,17505],"noopener","noreferrer","linear_regression",[29,17508],{},[53,17510,6795],{"id":17511},"clasificación",[2073,17513,17514],{},[12,17515,7111,17516,133],{},[40,17517,7114],{},[12,17519,17520],{},"Un problema de clasificacion busca predecir una variable de salida categórica a partir de un conjunto de variables independientes. Por ejemplo, predecir si un correo electrónico es spam o no spam basándose en su contenido, o saber si en la foto hay un gato o un perro.",[12,17522,17523],{},"Existen tres tipos principales de clasificación:",[1359,17525,17526,17532,17538],{},[1362,17527,17528,17531],{},[40,17529,17530],{},"Clasificación Binaria",": Cuando hay dos clases posibles. Por ejemplo, clasificar si un paciente tiene una enfermedad (sí\u002Fno).",[1362,17533,17534,17537],{},[40,17535,17536],{},"Clasificación Multiclase",": Cuando hay más de dos clases posibles. Por ejemplo, clasificar el tipo de flor (puede ser setosa, versicolor o virginica) basándose en sus características.",[1362,17539,17540,17543],{},[40,17541,17542],{},"Clasificación Multietiqueta",": Cuando cada ejemplo puede pertenecer a múltiples clases, como clasificar las etiquetas de un artículo de noticias (política, economía, deportes) donde un artículo puede pertenecer a varias categorías.",[2073,17545,17546],{},[12,17547,17548],{},"La diferencia entre clasificación multiclase y multietiqueta es que en la primera cada ejemplo solo puede pertenecer a una clase, mientras que en la segunda un ejemplo puede pertenecer a múltiples clases simultáneamente.",[12,17550,17551],{},"Veámos un poco más sobre la clasificación binaria. En este caso, el objetivo es encontrar una función que mapee las entradas a una de las dos clases posibles.",[12,17553,17554,17555,17558,17559,17673],{},"La pregunta que el modelo de clasificación binaria intenta responder es: ",[40,17556,17557],{},"¿Cuál es la probabilidad de que un ejemplo pertenezca a la clase 1 dado un conjunto de características?"," Esto se puede expresar matemáticamente como:\n",[83,17560,17562,17602],{"className":17561},[2151],[83,17563,17565],{"className":17564},[2155],[2157,17566,17567],{"xmlns":2159},[2162,17568,17569,17599],{},[2165,17570,17571,17574,17576,17578,17580,17582,17585,17587,17589,17591,17593,17595,17597],{},[2178,17572,17573],{},"P",[2172,17575,187],{"stretchy":6169},[2178,17577,3972],{},[2172,17579,229],{},[2182,17581,1161],{},[2178,17583,17584],{"mathvariant":689},"∣",[2178,17586,1640],{},[2172,17588,534],{"stretchy":6169},[2172,17590,229],{},[2178,17592,3604],{},[2172,17594,187],{"stretchy":6169},[2178,17596,1640],{},[2172,17598,534],{"stretchy":6169},[2214,17600,17601],{"encoding":2216},"P(y=1|x) = f(x)",[83,17603,17605,17630,17655],{"className":17604,"ariaHidden":2204},[2221],[83,17606,17608,17611,17615,17618,17621,17624,17627],{"className":17607},[2225],[83,17609],{"className":17610,"style":6250},[2229],[83,17612,17573],{"className":17613,"style":17614},[2234,2264],"margin-right:0.1389em;",[83,17616,187],{"className":17617},[6254],[83,17619,3972],{"className":17620,"style":6311},[2234,2264],[83,17622],{"className":17623,"style":2243},[2242],[83,17625,229],{"className":17626},[2247],[83,17628],{"className":17629,"style":2243},[2242],[83,17631,17633,17636,17640,17643,17646,17649,17652],{"className":17632},[2225],[83,17634],{"className":17635,"style":6250},[2229],[83,17637,17639],{"className":17638},[2234],"1∣",[83,17641,1640],{"className":17642},[2234,2264],[83,17644,534],{"className":17645},[6350],[83,17647],{"className":17648,"style":2243},[2242],[83,17650,229],{"className":17651},[2247],[83,17653],{"className":17654,"style":2243},[2242],[83,17656,17658,17661,17664,17667,17670],{"className":17657},[2225],[83,17659],{"className":17660,"style":6250},[2229],[83,17662,3604],{"className":17663,"style":6748},[2234,2264],[83,17665,187],{"className":17666},[6254],[83,17668,1640],{"className":17669},[2234,2264],[83,17671,534],{"className":17672},[6350],"\nDonde:",[1359,17675,17676,17752],{},[1362,17677,17678,17751],{},[83,17679,17681,17709],{"className":17680},[2151],[83,17682,17684],{"className":17683},[2155],[2157,17685,17686],{"xmlns":2159},[2162,17687,17688,17706],{},[2165,17689,17690,17692,17694,17696,17698,17700,17702,17704],{},[2178,17691,17573],{},[2172,17693,187],{"stretchy":6169},[2178,17695,3972],{},[2172,17697,229],{},[2182,17699,1161],{},[2178,17701,17584],{"mathvariant":689},[2178,17703,1640],{},[2172,17705,534],{"stretchy":6169},[2214,17707,17708],{"encoding":2216},"P(y=1|x)",[83,17710,17712,17736],{"className":17711,"ariaHidden":2204},[2221],[83,17713,17715,17718,17721,17724,17727,17730,17733],{"className":17714},[2225],[83,17716],{"className":17717,"style":6250},[2229],[83,17719,17573],{"className":17720,"style":17614},[2234,2264],[83,17722,187],{"className":17723},[6254],[83,17725,3972],{"className":17726,"style":6311},[2234,2264],[83,17728],{"className":17729,"style":2243},[2242],[83,17731,229],{"className":17732},[2247],[83,17734],{"className":17735,"style":2243},[2242],[83,17737,17739,17742,17745,17748],{"className":17738},[2225],[83,17740],{"className":17741,"style":6250},[2229],[83,17743,17639],{"className":17744},[2234],[83,17746,1640],{"className":17747},[2234,2264],[83,17749,534],{"className":17750},[6350]," es la probabilidad de que la clase sea 1 dado el vector de características x.",[1362,17753,17754,17798],{},[83,17755,17757,17777],{"className":17756},[2151],[83,17758,17760],{"className":17759},[2155],[2157,17761,17762],{"xmlns":2159},[2162,17763,17764,17774],{},[2165,17765,17766,17768,17770,17772],{},[2178,17767,3604],{},[2172,17769,187],{"stretchy":6169},[2178,17771,1640],{},[2172,17773,534],{"stretchy":6169},[2214,17775,17776],{"encoding":2216},"f(x)",[83,17778,17780],{"className":17779,"ariaHidden":2204},[2221],[83,17781,17783,17786,17789,17792,17795],{"className":17782},[2225],[83,17784],{"className":17785,"style":6250},[2229],[83,17787,3604],{"className":17788,"style":6748},[2234,2264],[83,17790,187],{"className":17791},[6254],[83,17793,1640],{"className":17794},[2234,2264],[83,17796,534],{"className":17797},[6350]," es la función que mapea las características a la probabilidad.",[12,17800,17801,17802,17805],{},"El modelo más común para clasificación binaria es la ",[40,17803,17804],{},"regresión logística",", que tiene el siguiente proceso:",[1406,17807,17808],{},[1362,17809,17810,17811,17814],{},"Calculamos una ",[40,17812,17813],{},"combinación lineal"," de las características:",[83,17816,17818],{"className":17817},[2147],[83,17819,17821,17894],{"className":17820},[2151],[83,17822,17824],{"className":17823},[2155],[2157,17825,17826],{"xmlns":2159,"display":2160},[2162,17827,17828,17891],{},[2165,17829,17830,17833,17835,17841,17843,17849,17855,17857,17863,17869,17871,17873,17875,17877,17879,17885],{},[2178,17831,17832],{},"z",[2172,17834,229],{},[2175,17836,17837,17839],{},[2178,17838,2180],{},[2182,17840,411],{},[2172,17842,2186],{},[2175,17844,17845,17847],{},[2178,17846,2180],{},[2182,17848,1161],{},[2175,17850,17851,17853],{},[2178,17852,1640],{},[2182,17854,1161],{},[2172,17856,2186],{},[2175,17858,17859,17861],{},[2178,17860,2180],{},[2182,17862,1149],{},[2175,17864,17865,17867],{},[2178,17866,1640],{},[2182,17868,1149],{},[2172,17870,2186],{},[2178,17872,133],{"mathvariant":689},[2178,17874,133],{"mathvariant":689},[2178,17876,133],{"mathvariant":689},[2172,17878,2186],{},[2175,17880,17881,17883],{},[2178,17882,2180],{},[2178,17884,12],{},[2175,17886,17887,17889],{},[2178,17888,1640],{},[2178,17890,12],{},[2214,17892,17893],{"encoding":2216},"z = \\beta_0 + \\beta_1 x_1 + \\beta_2 x_2 + ... + \\beta_p x_p",[83,17895,17897,17916,17971,18066,18161,18179],{"className":17896,"ariaHidden":2204},[2221],[83,17898,17900,17903,17907,17910,17913],{"className":17899},[2225],[83,17901],{"className":17902,"style":7592},[2229],[83,17904,17832],{"className":17905,"style":17906},[2234,2264],"margin-right:0.044em;",[83,17908],{"className":17909,"style":2243},[2242],[83,17911,229],{"className":17912},[2247],[83,17914],{"className":17915,"style":2243},[2242],[83,17917,17919,17922,17962,17965,17968],{"className":17918},[2225],[83,17920],{"className":17921,"style":2257},[2229],[83,17923,17925,17928],{"className":17924},[2234],[83,17926,2180],{"className":17927,"style":2265},[2234,2264],[83,17929,17931],{"className":17930},[2269],[83,17932,17934,17954],{"className":17933},[2273,2274],[83,17935,17937,17951],{"className":17936},[2278],[83,17938,17940],{"className":17939,"style":2283},[2282],[83,17941,17942,17945],{"style":2286},[83,17943],{"className":17944,"style":2291},[2290],[83,17946,17948],{"className":17947},[2295,2296,2297,2298],[83,17949,411],{"className":17950},[2234,2298],[83,17952,2306],{"className":17953},[2305],[83,17955,17957],{"className":17956},[2278],[83,17958,17960],{"className":17959,"style":2313},[2282],[83,17961],{},[83,17963],{"className":17964,"style":2319},[2242],[83,17966,2186],{"className":17967},[2323],[83,17969],{"className":17970,"style":2319},[2242],[83,17972,17974,17977,18017,18057,18060,18063],{"className":17973},[2225],[83,17975],{"className":17976,"style":2257},[2229],[83,17978,17980,17983],{"className":17979},[2234],[83,17981,2180],{"className":17982,"style":2265},[2234,2264],[83,17984,17986],{"className":17985},[2269],[83,17987,17989,18009],{"className":17988},[2273,2274],[83,17990,17992,18006],{"className":17991},[2278],[83,17993,17995],{"className":17994,"style":2283},[2282],[83,17996,17997,18000],{"style":2286},[83,17998],{"className":17999,"style":2291},[2290],[83,18001,18003],{"className":18002},[2295,2296,2297,2298],[83,18004,1161],{"className":18005},[2234,2298],[83,18007,2306],{"className":18008},[2305],[83,18010,18012],{"className":18011},[2278],[83,18013,18015],{"className":18014,"style":2313},[2282],[83,18016],{},[83,18018,18020,18023],{"className":18019},[2234],[83,18021,1640],{"className":18022},[2234,2264],[83,18024,18026],{"className":18025},[2269],[83,18027,18029,18049],{"className":18028},[2273,2274],[83,18030,18032,18046],{"className":18031},[2278],[83,18033,18035],{"className":18034,"style":2283},[2282],[83,18036,18037,18040],{"style":6276},[83,18038],{"className":18039,"style":2291},[2290],[83,18041,18043],{"className":18042},[2295,2296,2297,2298],[83,18044,1161],{"className":18045},[2234,2298],[83,18047,2306],{"className":18048},[2305],[83,18050,18052],{"className":18051},[2278],[83,18053,18055],{"className":18054,"style":2313},[2282],[83,18056],{},[83,18058],{"className":18059,"style":2319},[2242],[83,18061,2186],{"className":18062},[2323],[83,18064],{"className":18065,"style":2319},[2242],[83,18067,18069,18072,18112,18152,18155,18158],{"className":18068},[2225],[83,18070],{"className":18071,"style":2257},[2229],[83,18073,18075,18078],{"className":18074},[2234],[83,18076,2180],{"className":18077,"style":2265},[2234,2264],[83,18079,18081],{"className":18080},[2269],[83,18082,18084,18104],{"className":18083},[2273,2274],[83,18085,18087,18101],{"className":18086},[2278],[83,18088,18090],{"className":18089,"style":2283},[2282],[83,18091,18092,18095],{"style":2286},[83,18093],{"className":18094,"style":2291},[2290],[83,18096,18098],{"className":18097},[2295,2296,2297,2298],[83,18099,1149],{"className":18100},[2234,2298],[83,18102,2306],{"className":18103},[2305],[83,18105,18107],{"className":18106},[2278],[83,18108,18110],{"className":18109,"style":2313},[2282],[83,18111],{},[83,18113,18115,18118],{"className":18114},[2234],[83,18116,1640],{"className":18117},[2234,2264],[83,18119,18121],{"className":18120},[2269],[83,18122,18124,18144],{"className":18123},[2273,2274],[83,18125,18127,18141],{"className":18126},[2278],[83,18128,18130],{"className":18129,"style":2283},[2282],[83,18131,18132,18135],{"style":6276},[83,18133],{"className":18134,"style":2291},[2290],[83,18136,18138],{"className":18137},[2295,2296,2297,2298],[83,18139,1149],{"className":18140},[2234,2298],[83,18142,2306],{"className":18143},[2305],[83,18145,18147],{"className":18146},[2278],[83,18148,18150],{"className":18149,"style":2313},[2282],[83,18151],{},[83,18153],{"className":18154,"style":2319},[2242],[83,18156,2186],{"className":18157},[2323],[83,18159],{"className":18160,"style":2319},[2242],[83,18162,18164,18167,18170,18173,18176],{"className":18163},[2225],[83,18165],{"className":18166,"style":7476},[2229],[83,18168,6458],{"className":18169},[2234],[83,18171],{"className":18172,"style":2319},[2242],[83,18174,2186],{"className":18175},[2323],[83,18177],{"className":18178,"style":2319},[2242],[83,18180,18182,18185,18225],{"className":18181},[2225],[83,18183],{"className":18184,"style":7495},[2229],[83,181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de 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son las características o variables independientes.",[1362,19568,19569,17751],{},[83,19570,19572,19599],{"className":19571},[2151],[83,19573,19575],{"className":19574},[2155],[2157,19576,19577],{"xmlns":2159},[2162,19578,19579,19597],{},[2165,19580,19581,19583,19585,19587,19589,19591,19593,19595],{},[2178,19582,17573],{},[2172,19584,187],{"stretchy":6169},[2178,19586,3972],{},[2172,19588,229],{},[2182,19590,1161],{},[2178,19592,17584],{"mathvariant":689},[2178,19594,1640],{},[2172,19596,534],{"stretchy":6169},[2214,19598,17708],{"encoding":2216},[83,19600,19602,19626],{"className":19601,"ariaHidden":2204},[2221],[83,19603,19605,19608,19611,19614,19617,19620,19623],{"className":19604},[2225],[83,19606],{"className":19607,"style":6250},[2229],[83,19609,17573],{"className":19610,"style":17614},[2234,2264],[83,19612,187],{"className":19613},[6254],[83,19615,3972],{"className":19616,"style":6311},[2234,2264],[83,19618],{"className":19619,"style":2243},[2242],[83,19621,229],{"className":19622},[2247],[83,19624],{"className":19625,"style":2243},[2242],[83,19627,19629,19632,19635,19638],{"className":19628},[2225],[83,19630],{"className":19631,"style":6250},[2229],[83,19633,17639],{"className":19634},[2234],[83,19636,1640],{"className":19637},[2234,2264],[83,19639,534],{"className":19640},[6350],[12,19642,19643],{},"Cada característica aporta evidencia a favor o en contra, imagina si la palabra \"gratis\" aparece en un correo electrónico, eso podría aumentar la probabilidad de que sea spam. Por otro lado, si la palabra \"reunión\" aparece, eso podría disminuir la probabilidad de que sea spam.",[2073,19645,19646],{},[12,19647,19648],{},"Esto nos proporciona no solo una clasificación, sino también una medida de confianza en esa clasificación a través de la probabilidad calculada por la función sigmoide.",[12,19650,19651],{},"La función sigmoide transforma cualquier valor real en un valor entre 0 y 1. La fórmula como se muestra arriba es:",[83,19653,19655],{"className":19654},[2147],[83,19656,19658,19699],{"className":19657},[2151],[83,19659,19661],{"className":19660},[2155],[2157,19662,19663],{"xmlns":2159,"display":2160},[2162,19664,19665,19697],{},[2165,19666,19667,19669,19671,19673,19675,19677],{},[2178,19668,18291],{},[2172,19670,187],{"stretchy":6169},[2178,19672,17832],{},[2172,19674,534],{"stretchy":6169},[2172,19676,229],{},[9249,19678,19679,19681],{},[2182,19680,1161],{},[2165,19682,19683,19685,19687],{},[2182,19684,1161],{},[2172,19686,2186],{},[3702,19688,19689,19691],{},[2178,19690,16513],{},[2165,19692,19693,19695],{},[2172,19694,8650],{},[2178,19696,17832],{},[2214,19698,18322],{"encoding":2216},[83,19700,19702,19729],{"className":19701,"ariaHidden":2204},[2221],[83,19703,19705,19708,19711,19714,19717,19720,19723,19726],{"className":19704},[2225],[83,19706],{"className":19707,"style":6250},[2229],[83,19709,18291],{"className":19710,"style":6311},[2234,2264],[83,19712,187],{"className":19713},[6254],[83,19715,17832],{"className":19716,"style":17906},[2234,2264],[83,19718,534],{"className":19719},[6350],[83,19721],{"className":19722,"style":2243},[2242],[83,19724,229],{"className":19725},[2247],[83,19727],{"className":19728,"style":2243},[2242],[83,19730,19732,19735],{"className":19731},[2225],[83,19733],{"className":19734,"style":18359},[2229],[83,19736,19738,19741,19838],{"className":19737},[2234],[83,19739],{"className":19740},[6254,9342],[83,19742,19744],{"className":19743},[9249],[83,19745,19747,19830],{"className":19746},[2273,2274],[83,19748,19750,19827],{"className":19749},[2278],[83,19751,19753,19808,19816],{"className":19752,"style":9355},[2282],[83,19754,19755,19758],{"style":9358},[83,19756],{"className":19757,"style":2414},[2290],[83,19759,19761,19764,19767,19770,19773],{"className":19760},[2234],[83,19762,1161],{"className":19763},[2234],[83,19765],{"className":19766,"style":2319},[2242],[83,19768,2186],{"className":19769},[2323],[83,19771],{"className":19772,"style":2319},[2242],[83,19774,19776,19779],{"className":19775},[2234],[83,19777,16513],{"className":19778},[2234,2264],[83,19780,19782],{"className":19781},[2269],[83,19783,19785],{"className":19784},[2273],[83,19786,19788],{"className":19787},[2278],[83,19789,19791],{"className":19790,"style":18416},[2282],[83,19792,19793,19796],{"style":11191},[83,19794],{"className":19795,"style":2291},[2290],[83,19797,19799],{"className":19798},[2295,2296,2297,2298],[83,19800,19802,19805],{"className":19801},[2234,2298],[83,19803,8650],{"className":19804},[2234,2298],[83,19806,17832],{"className":19807,"style":17906},[2234,2264,2298],[83,19809,19810,19813],{"style":9370},[83,19811],{"className":19812,"style":2414},[2290],[83,19814],{"className":19815,"style":9378},[9377],[83,19817,19818,19821],{"style":9381},[83,19819],{"className":19820,"style":2414},[2290],[83,19822,19824],{"className":19823},[2234],[83,19825,1161],{"className":19826},[2234],[83,19828,2306],{"className":19829},[2305],[83,19831,19833],{"className":19832},[2278],[83,19834,19836],{"className":19835,"style":18462},[2282],[83,19837],{},[83,19839],{"className":19840},[6350,9342],[12,19842,7598],{},[1359,19844,19845,20320,20351],{},[1362,19846,19847,19875,19876,133],{},[83,19848,19850,19863],{"className":19849},[2151],[83,19851,19853],{"className":19852},[2155],[2157,19854,19855],{"xmlns":2159},[2162,19856,19857,19861],{},[2165,19858,19859],{},[2178,19860,17832],{},[2214,19862,17832],{"encoding":2216},[83,19864,19866],{"className":19865,"ariaHidden":2204},[2221],[83,19867,19869,19872],{"className":19868},[2225],[83,19870],{"className":19871,"style":7592},[2229],[83,19873,17832],{"className":19874,"style":17906},[2234,2264]," es la combinación lineal de las características, es decir, ",[83,19877,19879,19950],{"className":19878},[2151],[83,19880,19882],{"className":19881},[2155],[2157,19883,19884],{"xmlns":2159},[2162,19885,19886,19948],{},[2165,19887,19888,19890,19892,19898,19900,19906,19912,19914,19920,19926,19928,19930,19932,19934,19936,19942],{},[2178,19889,17832],{},[2172,19891,229],{},[2175,19893,19894,19896],{},[2178,19895,2180],{},[2182,19897,411],{},[2172,19899,2186],{},[2175,19901,19902,19904],{},[2178,19903,2180],{},[2182,19905,1161],{},[2175,19907,19908,19910],{},[2178,19909,1640],{},[2182,19911,1161],{},[2172,19913,2186],{},[2175,19915,19916,19918],{},[2178,19917,2180],{},[2182,19919,1149],{},[2175,19921,19922,19924],{},[2178,19923,1640],{},[2182,19925,1149],{},[2172,19927,2186],{},[2178,19929,133],{"mathvariant":689},[2178,19931,133],{"mathvariant":689},[2178,19933,133],{"mathvariant":689},[2172,19935,2186],{},[2175,19937,19938,19940],{},[2178,19939,2180],{},[2178,19941,12],{},[2175,19943,19944,19946],{},[2178,19945,1640],{},[2178,19947,12],{},[2214,19949,17893],{"encoding":2216},[83,19951,19953,19971,20026,20121,20216,20234],{"className":19952,"ariaHidden":2204},[2221],[83,19954,19956,19959,19962,19965,19968],{"className":19955},[2225],[83,19957],{"className":19958,"style":7592},[2229],[83,19960,17832],{"className":19961,"style":17906},[2234,2264],[83,19963],{"className":19964,"style":2243},[2242],[83,19966,229],{"className":19967},[2247],[83,19969],{"className":19970,"style":2243},[2242],[83,19972,19974,19977,20017,20020,20023],{"className":19973},[2225],[83,19975],{"className":19976,"style":2257},[2229],[83,19978,19980,19983],{"className":19979},[2234],[83,19981,2180],{"className":19982,"style":2265},[2234,2264],[83,19984,19986],{"className":19985},[2269],[83,19987,19989,20009],{"className":19988},[2273,2274],[83,19990,19992,20006],{"className":19991},[2278],[83,19993,19995],{"className":19994,"style":2283},[2282],[83,19996,19997,20000],{"style":2286},[83,19998],{"className":19999,"style":2291},[2290],[83,20001,20003],{"className":20002},[2295,2296,2297,2298],[83,20004,411],{"className":20005},[2234,2298],[83,20007,2306],{"className":20008},[2305],[83,20010,20012],{"className":20011},[2278],[83,20013,20015],{"className":20014,"style":2313},[2282],[83,20016],{},[83,20018],{"className":20019,"style":2319},[2242],[83,20021,2186],{"className":20022},[2323],[83,20024],{"className":20025,"style":2319},[2242],[83,20027,20029,20032,20072,20112,20115,20118],{"className":20028},[2225],[83,20030],{"className":20031,"style":2257},[2229],[83,20033,20035,20038],{"className":20034},[2234],[83,20036,2180],{"className":20037,"style":2265},[2234,2264],[83,20039,20041],{"className":20040},[2269],[83,20042,20044,20064],{"className":20043},[2273,2274],[83,20045,20047,20061],{"className":20046},[2278],[83,20048,20050],{"className":20049,"style":2283},[2282],[83,20051,20052,20055],{"style":2286},[83,20053],{"className":20054,"style":2291},[2290],[83,20056,20058],{"className":20057},[2295,2296,2297,2298],[83,20059,1161],{"className":20060},[2234,2298],[83,20062,2306],{"className":20063},[2305],[83,20065,20067],{"className":20066},[2278],[83,20068,20070],{"className":20069,"style":2313},[2282],[83,20071],{},[83,20073,20075,20078],{"className":20074},[2234],[83,20076,1640],{"className":20077},[2234,2264],[83,20079,20081],{"className":20080},[2269],[83,20082,20084,20104],{"className":20083},[2273,2274],[83,20085,20087,20101],{"className":20086},[2278],[83,20088,20090],{"className":20089,"style":2283},[2282],[83,20091,20092,20095],{"style":6276},[83,20093],{"className":20094,"style":2291},[2290],[83,20096,20098],{"className":20097},[2295,2296,2297,2298],[83,20099,1161],{"className":20100},[2234,2298],[83,20102,2306],{"className":20103},[2305],[83,20105,20107],{"className":20106},[2278],[83,20108,20110],{"className":20109,"style":2313},[2282],[83,20111],{},[83,20113],{"className":20114,"style":2319},[2242],[83,20116,2186],{"className":20117},[2323],[83,20119],{"className":20120,"style":2319},[2242],[83,20122,20124,20127,20167,20207,20210,20213],{"className":20123},[2225],[83,20125],{"className":20126,"style":2257},[2229],[83,20128,20130,20133],{"className":20129},[2234],[83,20131,2180],{"className":20132,"style":2265},[2234,2264],[83,20134,20136],{"className":20135},[2269],[83,20137,20139,20159],{"className":20138},[2273,2274],[83,20140,20142,20156],{"className":20141},[2278],[83,20143,20145],{"className":20144,"style":2283},[2282],[83,20146,20147,20150],{"style":2286},[83,20148],{"className":20149,"style":2291},[2290],[83,20151,20153],{"className":20152},[2295,2296,2297,2298],[83,20154,1149],{"className":20155},[2234,2298],[83,20157,2306],{"className":20158},[2305],[83,20160,20162],{"className":20161},[2278],[83,20163,20165],{"className":20164,"style":2313},[2282],[83,20166],{},[83,20168,20170,20173],{"className":20169},[2234],[83,20171,1640],{"className":20172},[2234,2264],[83,20174,20176],{"className":20175},[2269],[83,20177,20179,20199],{"className":20178},[2273,2274],[83,20180,20182,20196],{"className":20181},[2278],[83,20183,20185],{"className":20184,"style":2283},[2282],[83,20186,20187,20190],{"style":6276},[83,20188],{"className":20189,"style":2291},[2290],[83,20191,20193],{"className":20192},[2295,2296,2297,2298],[83,20194,1149],{"className":20195},[2234,2298],[83,20197,2306],{"className":20198},[2305],[83,20200,20202],{"className":20201},[2278],[83,20203,20205],{"className":20204,"style":2313},[2282],[83,20206],{},[83,20208],{"className":20209,"style":2319},[2242],[83,20211,2186],{"className":20212},[2323],[83,20214],{"className":20215,"style":2319},[2242],[83,20217,20219,20222,20225,20228,20231],{"className":20218},[2225],[83,20220],{"className":20221,"style":7476},[2229],[83,20223,6458],{"className":20224},[2234],[83,20226],{"className":20227,"style":2319},[2242],[83,20229,2186],{"className":20230},[2323],[83,20232],{"className":20233,"style":2319},[2242],[83,20235,20237,20240,20280],{"className":20236},[2225],[83,20238],{"className":20239,"style":7495},[2229],[83,20241,20243,20246],{"className":20242},[2234],[83,20244,2180],{"className":20245,"style":2265},[2234,2264],[83,20247,20249],{"className":20248},[2269],[83,20250,20252,20272],{"className":20251},[2273,2274],[83,20253,20255,20269],{"className":20254},[2278],[83,20256,20258],{"className":20257,"style":6486},[2282],[83,20259,20260,20263],{"style":2286},[83,20261],{"className":20262,"style":2291},[2290],[83,20264,20266],{"className":20265},[2295,2296,2297,2298],[83,20267,12],{"className":20268},[2234,2264,2298],[83,20270,2306],{"className":20271},[2305],[83,20273,20275],{"className":20274},[2278],[83,20276,20278],{"className":20277,"style":7534},[2282],[83,20279],{},[83,20281,20283,20286],{"className":20282},[2234],[83,20284,1640],{"className":20285},[2234,2264],[83,20287,20289],{"className":20288},[2269],[83,20290,20292,20312],{"className":20291},[2273,2274],[83,20293,20295,20309],{"className":20294},[2278],[83,20296,20298],{"className":20297,"style":6486},[2282],[83,20299,20300,20303],{"style":6276},[83,20301],{"className":20302,"style":2291},[2290],[83,20304,20306],{"className":20305},[2295,2296,2297,2298],[83,20307,12],{"className":20308},[2234,2264,2298],[83,20310,2306],{"className":20311},[2305],[83,20313,20315],{"className":20314},[2278],[83,20316,20318],{"className":20317,"style":7534},[2282],[83,20319],{},[1362,20321,20322,20350],{},[83,20323,20325,20338],{"className":20324},[2151],[83,20326,20328],{"className":20327},[2155],[2157,20329,20330],{"xmlns":2159},[2162,20331,20332,20336],{},[2165,20333,20334],{},[2178,20335,16513],{},[2214,20337,16513],{"encoding":2216},[83,20339,20341],{"className":20340,"ariaHidden":2204},[2221],[83,20342,20344,20347],{"className":20343},[2225],[83,20345],{"className":20346,"style":7592},[2229],[83,20348,16513],{"className":20349},[2234,2264]," es el número de Euler, aproximadamente igual a 2.71828.",[1362,20352,20353,20397],{},[83,20354,20356,20376],{"className":20355},[2151],[83,20357,20359],{"className":20358},[2155],[2157,20360,20361],{"xmlns":2159},[2162,20362,20363,20373],{},[2165,20364,20365,20367,20369,20371],{},[2178,20366,18291],{},[2172,20368,187],{"stretchy":6169},[2178,20370,17832],{},[2172,20372,534],{"stretchy":6169},[2214,20374,20375],{"encoding":2216},"\\sigma(z)",[83,20377,20379],{"className":20378,"ariaHidden":2204},[2221],[83,20380,20382,20385,20388,20391,20394],{"className":20381},[2225],[83,20383],{"className":20384,"style":6250},[2229],[83,20386,18291],{"className":20387,"style":6311},[2234,2264],[83,20389,187],{"className":20390},[6254],[83,20392,17832],{"className":20393,"style":17906},[2234,2264],[83,20395,534],{"className":20396},[6350]," es la salida de la función sigmoide, que representa la probabilidad de que la clase sea 1 dado el valor de z (rango entre 0 y 1).",[12,20399,20400,20401,20444,20445,20449],{},"Visualmente es algo así (con z en el eje X y ",[83,20402,20404,20423],{"className":20403},[2151],[83,20405,20407],{"className":20406},[2155],[2157,20408,20409],{"xmlns":2159},[2162,20410,20411,20421],{},[2165,20412,20413,20415,20417,20419],{},[2178,20414,18291],{},[2172,20416,187],{"stretchy":6169},[2178,20418,17832],{},[2172,20420,534],{"stretchy":6169},[2214,20422,20375],{"encoding":2216},[83,20424,20426],{"className":20425,"ariaHidden":2204},[2221],[83,20427,20429,20432,20435,20438,20441],{"className":20428},[2225],[83,20430],{"className":20431,"style":6250},[2229],[83,20433,18291],{"className":20434,"style":6311},[2234,2264],[83,20436,187],{"className":20437},[6254],[83,20439,17832],{"className":20440,"style":17906},[2234,2264],[83,20442,534],{"className":20443},[6350]," en el eje Y):\n",[1882,20446],{"alt":20447,"src":20448},"Gráfico de la función sigmoide","\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations\u002Fshared\u002Fsigmoid-function.webp",[1887,20450,20451],{},"Gráfico de la Función Sigmoide",[12,20453,20454],{},"De aqui podemos sacar algunas conclusiones importantes:",[1359,20456,20457,20504,20551],{},[1362,20458,20459,20460,20503],{},"Cuando z es muy negativo, ",[83,20461,20463,20482],{"className":20462},[2151],[83,20464,20466],{"className":20465},[2155],[2157,20467,20468],{"xmlns":2159},[2162,20469,20470,20480],{},[2165,20471,20472,20474,20476,20478],{},[2178,20473,18291],{},[2172,20475,187],{"stretchy":6169},[2178,20477,17832],{},[2172,20479,534],{"stretchy":6169},[2214,20481,20375],{"encoding":2216},[83,20483,20485],{"className":20484,"ariaHidden":2204},[2221],[83,20486,20488,20491,20494,20497,20500],{"className":20487},[2225],[83,20489],{"className":20490,"style":6250},[2229],[83,20492,18291],{"className":20493,"style":6311},[2234,2264],[83,20495,187],{"className":20496},[6254],[83,20498,17832],{"className":20499,"style":17906},[2234,2264],[83,20501,534],{"className":20502},[6350]," se acerca a 0, lo que indica una baja probabilidad de que la clase sea 1.",[1362,20505,20506,20507,20550],{},"Cuando z es muy positivo, ",[83,20508,20510,20529],{"className":20509},[2151],[83,20511,20513],{"className":20512},[2155],[2157,20514,20515],{"xmlns":2159},[2162,20516,20517,20527],{},[2165,20518,20519,20521,20523,20525],{},[2178,20520,18291],{},[2172,20522,187],{"stretchy":6169},[2178,20524,17832],{},[2172,20526,534],{"stretchy":6169},[2214,20528,20375],{"encoding":2216},[83,20530,20532],{"className":20531,"ariaHidden":2204},[2221],[83,20533,20535,20538,20541,20544,20547],{"className":20534},[2225],[83,20536],{"className":20537,"style":6250},[2229],[83,20539,18291],{"className":20540,"style":6311},[2234,2264],[83,20542,187],{"className":20543},[6254],[83,20545,17832],{"className":20546,"style":17906},[2234,2264],[83,20548,534],{"className":20549},[6350]," se acerca a 1, lo que indica una alta probabilidad de que la clase sea 1.",[1362,20552,20553,20554,20597],{},"Cuando z es 0, ",[83,20555,20557,20576],{"className":20556},[2151],[83,20558,20560],{"className":20559},[2155],[2157,20561,20562],{"xmlns":2159},[2162,20563,20564,20574],{},[2165,20565,20566,20568,20570,20572],{},[2178,20567,18291],{},[2172,20569,187],{"stretchy":6169},[2178,20571,17832],{},[2172,20573,534],{"stretchy":6169},[2214,20575,20375],{"encoding":2216},[83,20577,20579],{"className":20578,"ariaHidden":2204},[2221],[83,20580,20582,20585,20588,20591,20594],{"className":20581},[2225],[83,20583],{"className":20584,"style":6250},[2229],[83,20586,18291],{"className":20587,"style":6311},[2234,2264],[83,20589,187],{"className":20590},[6254],[83,20592,17832],{"className":20593,"style":17906},[2234,2264],[83,20595,534],{"className":20596},[6350]," es 0.5, lo que indica una probabilidad igual de que la clase sea 0 o 1.",[12,20599,20600,20601,20604],{},"EL valor de 0.5 ",[40,20602,20603],{},"comunmente se utiliza como umbral",", de manera que:",[1359,20606,20607,20679],{},[1362,20608,20609,20610,20678],{},"Si ",[83,20611,20613,20639],{"className":20612},[2151],[83,20614,20616],{"className":20615},[2155],[2157,20617,20618],{"xmlns":2159},[2162,20619,20620,20636],{},[2165,20621,20622,20624,20626,20628,20630,20633],{},[2178,20623,18291],{},[2172,20625,187],{"stretchy":6169},[2178,20627,17832],{},[2172,20629,534],{"stretchy":6169},[2172,20631,20632],{},"≥",[2182,20634,20635],{},"0.5",[2214,20637,20638],{"encoding":2216},"\\sigma(z) \\geq 0.5",[83,20640,20642,20669],{"className":20641,"ariaHidden":2204},[2221],[83,20643,20645,20648,20651,20654,20657,20660,20663,20666],{"className":20644},[2225],[83,20646],{"className":20647,"style":6250},[2229],[83,20649,18291],{"className":20650,"style":6311},[2234,2264],[83,20652,187],{"className":20653},[6254],[83,20655,17832],{"className":20656,"style":17906},[2234,2264],[83,20658,534],{"className":20659},[6350],[83,20661],{"className":20662,"style":2243},[2242],[83,20664,20632],{"className":20665},[2247],[83,20667],{"className":20668,"style":2243},[2242],[83,20670,20672,20675],{"className":20671},[2225],[83,20673],{"className":20674,"style":14779},[2229],[83,20676,20635],{"className":20677},[2234],", se clasifica como clase 1.",[1362,20680,20609,20681,20747],{},[83,20682,20684,20708],{"className":20683},[2151],[83,20685,20687],{"className":20686},[2155],[2157,20688,20689],{"xmlns":2159},[2162,20690,20691,20705],{},[2165,20692,20693,20695,20697,20699,20701,20703],{},[2178,20694,18291],{},[2172,20696,187],{"stretchy":6169},[2178,20698,17832],{},[2172,20700,534],{"stretchy":6169},[2172,20702,955],{},[2182,20704,20635],{},[2214,20706,20707],{"encoding":2216},"\\sigma(z) \u003C 0.5",[83,20709,20711,20738],{"className":20710,"ariaHidden":2204},[2221],[83,20712,20714,20717,20720,20723,20726,20729,20732,20735],{"className":20713},[2225],[83,20715],{"className":20716,"style":6250},[2229],[83,20718,18291],{"className":20719,"style":6311},[2234,2264],[83,20721,187],{"className":20722},[6254],[83,20724,17832],{"className":20725,"style":17906},[2234,2264],[83,20727,534],{"className":20728},[6350],[83,20730],{"className":20731,"style":2243},[2242],[83,20733,955],{"className":20734},[2247],[83,20736],{"className":20737,"style":2243},[2242],[83,20739,20741,20744],{"className":20740},[2225],[83,20742],{"className":20743,"style":14779},[2229],[83,20745,20635],{"className":20746},[2234],", se clasifica como clase 0.",[2073,20749,20750,20753],{},[12,20751,20752],{},"Propiedades clave:",[1359,20754,20755,20758,20805],{},[1362,20756,20757],{},"Rango acotado entre 0 y 1",[1362,20759,20760,20761,20804],{},"Monotonía, si z aumenta, ",[83,20762,20764,20783],{"className":20763},[2151],[83,20765,20767],{"className":20766},[2155],[2157,20768,20769],{"xmlns":2159},[2162,20770,20771,20781],{},[2165,20772,20773,20775,20777,20779],{},[2178,20774,18291],{},[2172,20776,187],{"stretchy":6169},[2178,20778,17832],{},[2172,20780,534],{"stretchy":6169},[2214,20782,20375],{"encoding":2216},[83,20784,20786],{"className":20785,"ariaHidden":2204},[2221],[83,20787,20789,20792,20795,20798,20801],{"className":20788},[2225],[83,20790],{"className":20791,"style":6250},[2229],[83,20793,18291],{"className":20794,"style":6311},[2234,2264],[83,20796,187],{"className":20797},[6254],[83,20799,17832],{"className":20800,"style":17906},[2234,2264],[83,20802,534],{"className":20803},[6350]," también aumenta)",[1362,20806,20807,20808,20874,20875,1966,20927,20874,20993],{},"Asintótica, ",[83,20809,20811,20835],{"className":20810},[2151],[83,20812,20814],{"className":20813},[2155],[2157,20815,20816],{"xmlns":2159},[2162,20817,20818,20832],{},[2165,20819,20820,20822,20824,20826,20828,20830],{},[2178,20821,18291],{},[2172,20823,187],{"stretchy":6169},[2178,20825,17832],{},[2172,20827,534],{"stretchy":6169},[2172,20829,6729],{},[2182,20831,1161],{},[2214,20833,20834],{"encoding":2216},"\\sigma(z) \\to 1",[83,20836,20838,20865],{"className":20837,"ariaHidden":2204},[2221],[83,20839,20841,20844,20847,20850,20853,20856,20859,20862],{"className":20840},[2225],[83,20842],{"className":20843,"style":6250},[2229],[83,20845,18291],{"className":20846,"style":6311},[2234,2264],[83,20848,187],{"className":20849},[6254],[83,20851,17832],{"className":20852,"style":17906},[2234,2264],[83,20854,534],{"className":20855},[6350],[83,20857],{"className":20858,"style":2243},[2242],[83,20860,6729],{"className":20861},[2247],[83,20863],{"className":20864,"style":2243},[2242],[83,20866,20868,20871],{"className":20867},[2225],[83,20869],{"className":20870,"style":14779},[2229],[83,20872,1161],{"className":20873},[2234]," cuando ",[83,20876,20878,20897],{"className":20877},[2151],[83,20879,20881],{"className":20880},[2155],[2157,20882,20883],{"xmlns":2159},[2162,20884,20885,20894],{},[2165,20886,20887,20889,20891],{},[2178,20888,17832],{},[2172,20890,6729],{},[2178,20892,20893],{"mathvariant":689},"∞",[2214,20895,20896],{"encoding":2216},"z \\to \\infty",[83,20898,20900,20918],{"className":20899,"ariaHidden":2204},[2221],[83,20901,20903,20906,20909,20912,20915],{"className":20902},[2225],[83,20904],{"className":20905,"style":7592},[2229],[83,20907,17832],{"className":20908,"style":17906},[2234,2264],[83,20910],{"className":20911,"style":2243},[2242],[83,20913,6729],{"className":20914},[2247],[83,20916],{"className":20917,"style":2243},[2242],[83,20919,20921,20924],{"className":20920},[2225],[83,20922],{"className":20923,"style":7592},[2229],[83,20925,20893],{"className":20926},[2234],[83,20928,20930,20954],{"className":20929},[2151],[83,20931,20933],{"className":20932},[2155],[2157,20934,20935],{"xmlns":2159},[2162,20936,20937,20951],{},[2165,20938,20939,20941,20943,20945,20947,20949],{},[2178,20940,18291],{},[2172,20942,187],{"stretchy":6169},[2178,20944,17832],{},[2172,20946,534],{"stretchy":6169},[2172,20948,6729],{},[2182,20950,411],{},[2214,20952,20953],{"encoding":2216},"\\sigma(z) \\to 0",[83,20955,20957,20984],{"className":20956,"ariaHidden":2204},[2221],[83,20958,20960,20963,20966,20969,20972,20975,20978,20981],{"className":20959},[2225],[83,20961],{"className":20962,"style":6250},[2229],[83,20964,18291],{"className":20965,"style":6311},[2234,2264],[83,20967,187],{"className":20968},[6254],[83,20970,17832],{"className":20971,"style":17906},[2234,2264],[83,20973,534],{"className":20974},[6350],[83,20976],{"className":20977,"style":2243},[2242],[83,20979,6729],{"className":20980},[2247],[83,20982],{"className":20983,"style":2243},[2242],[83,20985,20987,20990],{"className":20986},[2225],[83,20988],{"className":20989,"style":14779},[2229],[83,20991,411],{"className":20992},[2234],[83,20994,20996,21016],{"className":20995},[2151],[83,20997,20999],{"className":20998},[2155],[2157,21000,21001],{"xmlns":2159},[2162,21002,21003,21013],{},[2165,21004,21005,21007,21009,21011],{},[2178,21006,17832],{},[2172,21008,6729],{},[2172,21010,8650],{},[2178,21012,20893],{"mathvariant":689},[2214,21014,21015],{"encoding":2216},"z \\to -\\infty",[83,21017,21019,21037],{"className":21018,"ariaHidden":2204},[2221],[83,21020,21022,21025,21028,21031,21034],{"className":21021},[2225],[83,21023],{"className":21024,"style":7592},[2229],[83,21026,17832],{"className":21027,"style":17906},[2234,2264],[83,21029],{"className":21030,"style":2243},[2242],[83,21032,6729],{"className":21033},[2247],[83,21035],{"className":21036,"style":2243},[2242],[83,21038,21040,21043,21046],{"className":21039},[2225],[83,21041],{"className":21042,"style":7476},[2229],[83,21044,8650],{"className":21045},[2234],[83,21047,20893],{"className":21048},[2234],[12,21050,21051,21054,21055,21058,21059,624],{},[40,21052,21053],{},"¿Cómo medimos el error en clasificación?"," Aquí se utilizan métricas como la ",[40,21056,21057],{},"entropía cruzada"," o ",[40,21060,21061],{},"log loss",[12,21063,21064],{},"Pérdida para una muestra:",[83,21066,21068],{"className":21067},[2147],[83,21069,21071,21147],{"className":21070},[2151],[83,21072,21074],{"className":21073},[2155],[2157,21075,21076],{"xmlns":2159,"display":2160},[2162,21077,21078,21144],{},[2165,21079,21080,21083,21085,21087,21089,21091,21093,21096,21099,21101,21107,21109,21111,21113,21115,21117,21119,21121,21123,21125,21127,21129,21131,21133,21139,21141],{},[2178,21081,21082],{},"L",[2172,21084,229],{},[2172,21086,8650],{},[2172,21088,1481],{"stretchy":6169},[2178,21090,3972],{},[2172,21092,2195],{},[2178,21094,21095],{},"log",[2172,21097,21098],{},"⁡",[2172,21100,187],{"stretchy":6169},[2202,21102,21103,21105],{"accent":2204},[2178,21104,3972],{},[2172,21106,8661],{},[2172,21108,534],{"stretchy":6169},[2172,21110,2186],{},[2172,21112,187],{"stretchy":6169},[2182,21114,1161],{},[2172,21116,8650],{},[2178,21118,3972],{},[2172,21120,534],{"stretchy":6169},[2172,21122,2195],{},[2178,21124,21095],{},[2172,21126,21098],{},[2172,21128,187],{"stretchy":6169},[2182,21130,1161],{},[2172,21132,8650],{},[2202,21134,21135,21137],{"accent":2204},[2178,21136,3972],{},[2172,21138,8661],{},[2172,21140,534],{"stretchy":6169},[2172,21142,21143],{"stretchy":6169},"]",[2214,21145,21146],{"encoding":2216},"L = -[y \\cdot \\log(\\hat{y}) + (1 - y) \\cdot \\log(1 - \\hat{y})]",[83,21148,21150,21168,21192,21263,21284,21305,21331],{"className":21149,"ariaHidden":2204},[2221],[83,21151,21153,21156,21159,21162,21165],{"className":21152},[2225],[83,21154],{"className":21155,"style":2230},[2229],[83,21157,21082],{"className":21158},[2234,2264],[83,21160],{"className":21161,"style":2243},[2242],[83,21163,229],{"className":21164},[2247],[83,21166],{"className":21167,"style":2243},[2242],[83,21169,21171,21174,21177,21180,21183,21186,21189],{"className":21170},[2225],[83,21172],{"className":21173,"style":6250},[2229],[83,21175,8650],{"className":21176},[2234],[83,21178,1481],{"className":21179},[6254],[83,21181,3972],{"className":21182,"style":6311},[2234,2264],[83,21184],{"className":21185,"style":2319},[2242],[83,21187,2195],{"className":21188},[2323],[83,21190],{"className":21191,"style":2319},[2242],[83,21193,21195,21198,21206,21209,21251,21254,21257,21260],{"className":21194},[2225],[83,21196],{"className":21197,"style":6250},[2229],[83,21199,21201,21202],{"className":21200},[9412],"lo",[83,21203,21205],{"style":21204},"margin-right:0.0139em;","g",[83,21207,187],{"className":21208},[6254],[83,21210,21212],{"className":21211},[2234,2398],[83,21213,21215,21243],{"className":21214},[2273,2274],[83,21216,21218,21240],{"className":21217},[2278],[83,21219,21221,21229],{"className":21220,"style":2388},[2282],[83,21222,21223,21226],{"style":2410},[83,21224],{"className":21225,"style":2414},[2290],[83,21227,3972],{"className":21228,"style":6311},[2234,2264],[83,21230,21231,21234],{"style":2410},[83,21232],{"className":21233,"style":2414},[2290],[83,21235,21237],{"className":21236,"style":9858},[2426],[83,21238,8661],{"className":21239},[2234],[83,21241,2306],{"className":21242},[2305],[83,21244,21246],{"className":21245},[2278],[83,21247,21249],{"className":21248,"style":8875},[2282],[83,21250],{},[83,21252,534],{"className":21253},[6350],[83,21255],{"className":21256,"style":2319},[2242],[83,21258,2186],{"className":21259},[2323],[83,21261],{"className":21262,"style":2319},[2242],[83,21264,21266,21269,21272,21275,21278,21281],{"className":21265},[2225],[83,21267],{"className":21268,"style":6250},[2229],[83,21270,187],{"className":21271},[6254],[83,21273,1161],{"className":21274},[2234],[83,21276],{"className":21277,"style":2319},[2242],[83,21279,8650],{"className":21280},[2323],[83,21282],{"className":21283,"style":2319},[2242],[83,21285,21287,21290,21293,21296,21299,21302],{"className":21286},[2225],[83,21288],{"className":21289,"style":6250},[2229],[83,21291,3972],{"className":21292,"style":6311},[2234,2264],[83,21294,534],{"className":21295},[6350],[83,21297],{"className":21298,"style":2319},[2242],[83,21300,2195],{"className":21301},[2323],[83,21303],{"className":21304,"style":2319},[2242],[83,21306,21308,21311,21316,21319,21322,21325,21328],{"className":21307},[2225],[83,21309],{"className":21310,"style":6250},[2229],[83,21312,21201,21314],{"className":21313},[9412],[83,21315,21205],{"style":21204},[83,21317,187],{"className":21318},[6254],[83,21320,1161],{"className":21321},[2234],[83,21323],{"className":21324,"style":2319},[2242],[83,21326,8650],{"className":21327},[2323],[83,21329],{"className":21330,"style":2319},[2242],[83,21332,21334,21337,21379],{"className":21333},[2225],[83,21335],{"className":21336,"style":6250},[2229],[83,21338,21340],{"className":21339},[2234,2398],[83,21341,21343,21371],{"className":21342},[2273,2274],[83,21344,21346,21368],{"className":21345},[2278],[83,21347,21349,21357],{"className":21348,"style":2388},[2282],[83,21350,21351,21354],{"style":2410},[83,21352],{"className":21353,"style":2414},[2290],[83,21355,3972],{"className":21356,"style":6311},[2234,2264],[83,21358,21359,21362],{"style":2410},[83,21360],{"className":21361,"style":2414},[2290],[83,21363,21365],{"className":21364,"style":9858},[2426],[83,21366,8661],{"className":21367},[2234],[83,21369,2306],{"className":21370},[2305],[83,21372,21374],{"className":21373},[2278],[83,21375,21377],{"className":21376,"style":8875},[2282],[83,21378],{},[83,21380,21382],{"className":21381},[6350],")]",[12,21384,21385],{},"Pérdida promedio (o función de costo) para todo el conjunto de datos:",[83,21387,21389],{"className":21388},[2147],[83,21390,21392,21501],{"className":21391},[2151],[83,21393,21395],{"className":21394},[2155],[2157,21396,21397],{"xmlns":2159,"display":2160},[2162,21398,21399,21498],{},[2165,21400,21401,21404,21406,21408,21414,21428,21430,21436,21438,21440,21442,21444,21454,21456,21458,21460,21462,21464,21470,21472,21474,21476,21478,21480,21482,21484,21494,21496],{},[2178,21402,21403],{},"J",[2172,21405,229],{},[2172,21407,8650],{},[9249,21409,21410,21412],{},[2182,21411,1161],{},[2178,21413,313],{},[9256,21415,21416,21418,21426],{},[2172,21417,9260],{},[2165,21419,21420,21422,21424],{},[2178,21421,6578],{},[2172,21423,229],{},[2182,21425,1161],{},[2178,21427,313],{},[2172,21429,1481],{"stretchy":6169},[2175,21431,21432,21434],{},[2178,21433,3972],{},[2178,21435,6578],{},[2172,21437,2195],{},[2178,21439,21095],{},[2172,21441,21098],{},[2172,21443,187],{"stretchy":6169},[2202,21445,21446,21452],{"accent":2204},[2175,21447,21448,21450],{},[2178,21449,3972],{},[2178,21451,6578],{},[2172,21453,8661],{},[2172,21455,534],{"stretchy":6169},[2172,21457,2186],{},[2172,21459,187],{"stretchy":6169},[2182,21461,1161],{},[2172,21463,8650],{},[2175,21465,21466,21468],{},[2178,21467,3972],{},[2178,21469,6578],{},[2172,21471,534],{"stretchy":6169},[2172,21473,2195],{},[2178,21475,21095],{},[2172,21477,21098],{},[2172,21479,187],{"stretchy":6169},[2182,21481,1161],{},[2172,21483,8650],{},[2202,21485,21486,21492],{"accent":2204},[2175,21487,21488,21490],{},[2178,21489,3972],{},[2178,21491,6578],{},[2172,21493,8661],{},[2172,21495,534],{"stretchy":6169},[2172,21497,21143],{"stretchy":6169},[2214,21499,21500],{"encoding":2216},"J = -\\frac{1}{n} \\sum_{i=1}^{n} [y_i \\cdot \\log(\\hat{y_i}) + (1 - y_i) \\cdot \\log(1 - 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22092,22094,22108],{"className":22093},[2278],[83,22095,22097],{"className":22096,"style":6610},[2282],[83,22098,22099,22102],{"style":6326},[83,22100],{"className":22101,"style":2291},[2290],[83,22103,22105],{"className":22104},[2295,2296,2297,2298],[83,22106,6578],{"className":22107},[2234,2264,2298],[83,22109,2306],{"className":22110},[2305],[83,22112,22114],{"className":22113},[2278],[83,22115,22117],{"className":22116,"style":2313},[2282],[83,22118],{}," es la etiqueta real (0 o 1) para el ejemplo ",[83,22121,22123,22136],{"className":22122},[2151],[83,22124,22126],{"className":22125},[2155],[2157,22127,22128],{"xmlns":2159},[2162,22129,22130,22134],{},[2165,22131,22132],{},[2178,22133,6578],{},[2214,22135,6578],{"encoding":2216},[83,22137,22139],{"className":22138,"ariaHidden":2204},[2221],[83,22140,22142,22145],{"className":22141},[2225],[83,22143],{"className":22144,"style":9787},[2229],[83,22146,6578],{"className":22147},[2234,2264],[1362,22149,22150,22263,22264,22292],{},[83,22151,22153,22175],{"className":22152},[2151],[83,22154,22156],{"className":22155},[2155],[2157,22157,22158],{"xmlns":2159},[2162,22159,22160,22172],{},[2165,22161,22162],{},[2202,22163,22164,22170],{"accent":2204},[2175,22165,22166,22168],{},[2178,22167,3972],{},[2178,22169,6578],{},[2172,22171,8661],{},[2214,22173,22174],{"encoding":2216},"\\hat{y_i}",[83,22176,22178],{"className":22177,"ariaHidden":2204},[2221],[83,22179,22181,22184],{"className":22180},[2225],[83,22182],{"className":22183,"style":2257},[2229],[83,22185,22187],{"className":22186},[2234,2398],[83,22188,22190,22255],{"className":22189},[2273,2274],[83,22191,22193,22252],{"className":22192},[2278],[83,22194,22196,22241],{"className":22195,"style":2388},[2282],[83,22197,22198,22201],{"style":2410},[83,22199],{"className":22200,"style":2414},[2290],[83,22202,22204,22207],{"className":22203},[2234],[83,22205,3972],{"className":22206,"style":6311},[2234,2264],[83,22208,22210],{"className":22209},[2269],[83,22211,22213,22233],{"className":22212},[2273,2274],[83,22214,22216,22230],{"className":22215},[2278],[83,22217,22219],{"className":22218,"style":6610},[2282],[83,22220,22221,22224],{"style":6326},[83,22222],{"className":22223,"style":2291},[2290],[83,22225,22227],{"className":22226},[2295,2296,2297,2298],[83,22228,6578],{"className":22229},[2234,2264,2298],[83,22231,2306],{"className":22232},[2305],[83,22234,22236],{"className":22235},[2278],[83,22237,22239],{"className":22238,"style":2313},[2282],[83,22240],{},[83,22242,22243,22246],{"style":2410},[83,22244],{"className":22245,"style":2414},[2290],[83,22247,22249],{"className":22248,"style":2427},[2426],[83,22250,8661],{"className":22251},[2234],[83,22253,2306],{"className":22254},[2305],[83,22256,22258],{"className":22257},[2278],[83,22259,22261],{"className":22260,"style":8875},[2282],[83,22262],{}," es la probabilidad predicha por el modelo para el ejemplo ",[83,22265,22267,22280],{"className":22266},[2151],[83,22268,22270],{"className":22269},[2155],[2157,22271,22272],{"xmlns":2159},[2162,22273,22274,22278],{},[2165,22275,22276],{},[2178,22277,6578],{},[2214,22279,6578],{"encoding":2216},[83,22281,22283],{"className":22282,"ariaHidden":2204},[2221],[83,22284,22286,22289],{"className":22285},[2225],[83,22287],{"className":22288,"style":9787},[2229],[83,22290,6578],{"className":22291},[2234,2264]," (valor entre 0 y 1).",[12,22294,22295],{},"¿Por qué se usa la entropía cruzada?",[1406,22297,22298,22301,22304],{},[1362,22299,22300],{},"Penaliza más las predicciones incorrectas con alta confianza.",[1362,22302,22303],{},"Es una función de pérdida convexa, lo que facilita la optimización mediante métodos como el descenso de gradiente.",[1362,22305,22306],{},"Interpretación probabilística, ya que se basa en la probabilidad predicha por el modelo.",[12,22308,22309],{},"El comportamiento de la función de pérdida se muestra en la siguiente gráfica:",[12,22311,22312,22316],{},[1882,22313],{"alt":22314,"src":22315},"Gráfico de la función de pérdida de entropía cruzada","\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations\u002Fshared\u002Fcross-entropy.webp",[1887,22317,22318],{},"Gráfico de la Función de Pérdida de Entropía Cruzada",[12,22320,22321],{},"La función penaliza más las predicciones incorrectas con alta confianza, lo que se refleja en la forma de la curva.",[1406,22323,22324],{},[1362,22325,22326],{},"Cuando la etiqueta real es 1 (y=1) (línea azul):",[1359,22328,22329,22453,22528],{},[1362,22330,22331,22332],{},"La fórmula se simplifica a ",[83,22333,22335,22367],{"className":22334},[2151],[83,22336,22338],{"className":22337},[2155],[2157,22339,22340],{"xmlns":2159},[2162,22341,22342,22364],{},[2165,22343,22344,22346,22348,22350,22352,22354,22356,22362],{},[2178,22345,21082],{},[2172,22347,229],{},[2172,22349,8650],{},[2178,22351,21095],{},[2172,22353,21098],{},[2172,22355,187],{"stretchy":6169},[2202,22357,22358,22360],{"accent":2204},[2178,22359,3972],{},[2172,22361,8661],{},[2172,22363,534],{"stretchy":6169},[2214,22365,22366],{"encoding":2216},"L = -\\log(\\hat{y})",[83,22368,22370,22388],{"className":22369,"ariaHidden":2204},[2221],[83,22371,22373,22376,22379,22382,22385],{"className":22372},[2225],[83,22374],{"className":22375,"style":2230},[2229],[83,22377,21082],{"className":22378},[2234,2264],[83,22380],{"className":22381,"style":2243},[2242],[83,22383,229],{"className":22384},[2247],[83,22386],{"className":22387,"style":2243},[2242],[83,22389,22391,22394,22397,22400,22405,22408,22450],{"className":22390},[2225],[83,22392],{"className":22393,"style":6250},[2229],[83,22395,8650],{"className":22396},[2234],[83,22398],{"className":22399,"style":6304},[2242],[83,22401,21201,22403],{"className":22402},[9412],[83,22404,21205],{"style":21204},[83,22406,187],{"className":22407},[6254],[83,22409,22411],{"className":22410},[2234,2398],[83,22412,22414,22442],{"className":22413},[2273,2274],[83,22415,22417,22439],{"className":22416},[2278],[83,22418,22420,22428],{"className":22419,"style":2388},[2282],[83,22421,22422,22425],{"style":2410},[83,22423],{"className":22424,"style":2414},[2290],[83,22426,3972],{"className":22427,"style":6311},[2234,2264],[83,22429,22430,22433],{"style":2410},[83,22431],{"className":22432,"style":2414},[2290],[83,22434,22436],{"className":22435,"style":9858},[2426],[83,22437,8661],{"className":22438},[2234],[83,22440,2306],{"className":22441},[2305],[83,22443,22445],{"className":22444},[2278],[83,22446,22448],{"className":22447,"style":8875},[2282],[83,22449],{},[83,22451,534],{"className":22452},[6350],[1362,22454,20609,22455,22527],{},[83,22456,22458,22476],{"className":22457},[2151],[83,22459,22461],{"className":22460},[2155],[2157,22462,22463],{"xmlns":2159},[2162,22464,22465,22473],{},[2165,22466,22467],{},[2202,22468,22469,22471],{"accent":2204},[2178,22470,3972],{},[2172,22472,8661],{},[2214,22474,22475],{"encoding":2216},"\\hat{y}",[83,22477,22479],{"className":22478,"ariaHidden":2204},[2221],[83,22480,22482,22485],{"className":22481},[2225],[83,22483],{"className":22484,"style":2257},[2229],[83,22486,22488],{"className":22487},[2234,2398],[83,22489,22491,22519],{"className":22490},[2273,2274],[83,22492,22494,22516],{"className":22493},[2278],[83,22495,22497,22505],{"className":22496,"style":2388},[2282],[83,22498,22499,22502],{"style":2410},[83,22500],{"className":22501,"style":2414},[2290],[83,22503,3972],{"className":22504,"style":6311},[2234,2264],[83,22506,22507,22510],{"style":2410},[83,22508],{"className":22509,"style":2414},[2290],[83,22511,22513],{"className":22512,"style":9858},[2426],[83,22514,8661],{"className":22515},[2234],[83,22517,2306],{"className":22518},[2305],[83,22520,22522],{"className":22521},[2278],[83,22523,22525],{"className":22524,"style":8875},[2282],[83,22526],{}," se acerca a 1, la pérdida se acerca a 0 (buena predicción).",[1362,22529,20609,22530,22601],{},[83,22531,22533,22550],{"className":22532},[2151],[83,22534,22536],{"className":22535},[2155],[2157,22537,22538],{"xmlns":2159},[2162,22539,22540,22548],{},[2165,22541,22542],{},[2202,22543,22544,22546],{"accent":2204},[2178,22545,3972],{},[2172,22547,8661],{},[2214,22549,22475],{"encoding":2216},[83,22551,22553],{"className":22552,"ariaHidden":2204},[2221],[83,22554,22556,22559],{"className":22555},[2225],[83,22557],{"className":22558,"style":2257},[2229],[83,22560,22562],{"className":22561},[2234,2398],[83,22563,22565,22593],{"className":22564},[2273,2274],[83,22566,22568,22590],{"className":22567},[2278],[83,22569,22571,22579],{"className":22570,"style":2388},[2282],[83,22572,22573,22576],{"style":2410},[83,22574],{"className":22575,"style":2414},[2290],[83,22577,3972],{"className":22578,"style":6311},[2234,2264],[83,22580,22581,22584],{"style":2410},[83,22582],{"className":22583,"style":2414},[2290],[83,22585,22587],{"className":22586,"style":9858},[2426],[83,22588,8661],{"className":22589},[2234],[83,22591,2306],{"className":22592},[2305],[83,22594,22596],{"className":22595},[2278],[83,22597,22599],{"className":22598,"style":8875},[2282],[83,22600],{}," se acerca a 0, la pérdida se dispara a infinito (mala predicción).",[1406,22603,22604],{"start":103},[1362,22605,22606],{},"Cuando la etiqueta real es 0 (y=0) (línea roja):",[1359,22608,22609,22754,22828],{},[1362,22610,22331,22611],{},[83,22612,22614,22650],{"className":22613},[2151],[83,22615,22617],{"className":22616},[2155],[2157,22618,22619],{"xmlns":2159},[2162,22620,22621,22647],{},[2165,22622,22623,22625,22627,22629,22631,22633,22635,22637,22639,22645],{},[2178,22624,21082],{},[2172,22626,229],{},[2172,22628,8650],{},[2178,22630,21095],{},[2172,22632,21098],{},[2172,22634,187],{"stretchy":6169},[2182,22636,1161],{},[2172,22638,8650],{},[2202,22640,22641,22643],{"accent":2204},[2178,22642,3972],{},[2172,22644,8661],{},[2172,22646,534],{"stretchy":6169},[2214,22648,22649],{"encoding":2216},"L = -\\log(1 - \\hat{y})",[83,22651,22653,22671,22703],{"className":22652,"ariaHidden":2204},[2221],[83,22654,22656,22659,22662,22665,22668],{"className":22655},[2225],[83,22657],{"className":22658,"style":2230},[2229],[83,22660,21082],{"className":22661},[2234,2264],[83,22663],{"className":22664,"style":2243},[2242],[83,22666,229],{"className":22667},[2247],[83,22669],{"className":22670,"style":2243},[2242],[83,22672,22674,22677,22680,22683,22688,22691,22694,22697,22700],{"className":22673},[2225],[83,22675],{"className":22676,"style":6250},[2229],[83,22678,8650],{"className":22679},[2234],[83,22681],{"className":22682,"style":6304},[2242],[83,22684,21201,22686],{"className":22685},[9412],[83,22687,21205],{"style":21204},[83,22689,187],{"className":22690},[6254],[83,22692,1161],{"className":22693},[2234],[83,22695],{"className":22696,"style":2319},[2242],[83,22698,8650],{"className":22699},[2323],[83,22701],{"className":22702,"style":2319},[2242],[83,22704,22706,22709,22751],{"className":22705},[2225],[83,22707],{"className":22708,"style":6250},[2229],[83,22710,22712],{"className":22711},[2234,2398],[83,22713,22715,22743],{"className":22714},[2273,2274],[83,22716,22718,22740],{"className":22717},[2278],[83,22719,22721,22729],{"className":22720,"style":2388},[2282],[83,22722,22723,22726],{"style":2410},[83,22724],{"className":22725,"style":2414},[2290],[83,22727,3972],{"className":22728,"style":6311},[2234,2264],[83,22730,22731,22734],{"style":2410},[83,22732],{"className":22733,"style":2414},[2290],[83,22735,22737],{"className":22736,"style":9858},[2426],[83,22738,8661],{"className":22739},[2234],[83,22741,2306],{"className":22742},[2305],[83,22744,22746],{"className":22745},[2278],[83,22747,22749],{"className":22748,"style":8875},[2282],[83,22750],{},[83,22752,534],{"className":22753},[6350],[1362,22755,20609,22756,22827],{},[83,22757,22759,22776],{"className":22758},[2151],[83,22760,22762],{"className":22761},[2155],[2157,22763,22764],{"xmlns":2159},[2162,22765,22766,22774],{},[2165,22767,22768],{},[2202,22769,22770,22772],{"accent":2204},[2178,22771,3972],{},[2172,22773,8661],{},[2214,22775,22475],{"encoding":2216},[83,22777,22779],{"className":22778,"ariaHidden":2204},[2221],[83,22780,22782,22785],{"className":22781},[2225],[83,22783],{"className":22784,"style":2257},[2229],[83,22786,22788],{"className":22787},[2234,2398],[83,22789,22791,22819],{"className":22790},[2273,2274],[83,22792,22794,22816],{"className":22793},[2278],[83,22795,22797,22805],{"className":22796,"style":2388},[2282],[83,22798,22799,22802],{"style":2410},[83,22800],{"className":22801,"style":2414},[2290],[83,22803,3972],{"className":22804,"style":6311},[2234,2264],[83,22806,22807,22810],{"style":2410},[83,22808],{"className":22809,"style":2414},[2290],[83,22811,22813],{"className":22812,"style":9858},[2426],[83,22814,8661],{"className":22815},[2234],[83,22817,2306],{"className":22818},[2305],[83,22820,22822],{"className":22821},[2278],[83,22823,22825],{"className":22824,"style":8875},[2282],[83,22826],{}," se acerca a 0, la pérdida se acerca a 0 (buena predicción).",[1362,22829,20609,22830,22901],{},[83,22831,22833,22850],{"className":22832},[2151],[83,22834,22836],{"className":22835},[2155],[2157,22837,22838],{"xmlns":2159},[2162,22839,22840,22848],{},[2165,22841,22842],{},[2202,22843,22844,22846],{"accent":2204},[2178,22845,3972],{},[2172,22847,8661],{},[2214,22849,22475],{"encoding":2216},[83,22851,22853],{"className":22852,"ariaHidden":2204},[2221],[83,22854,22856,22859],{"className":22855},[2225],[83,22857],{"className":22858,"style":2257},[2229],[83,22860,22862],{"className":22861},[2234,2398],[83,22863,22865,22893],{"className":22864},[2273,2274],[83,22866,22868,22890],{"className":22867},[2278],[83,22869,22871,22879],{"className":22870,"style":2388},[2282],[83,22872,22873,22876],{"style":2410},[83,22874],{"className":22875,"style":2414},[2290],[83,22877,3972],{"className":22878,"style":6311},[2234,2264],[83,22880,22881,22884],{"style":2410},[83,22882],{"className":22883,"style":2414},[2290],[83,22885,22887],{"className":22886,"style":9858},[2426],[83,22888,8661],{"className":22889},[2234],[83,22891,2306],{"className":22892},[2305],[83,22894,22896],{"className":22895},[2278],[83,22897,22899],{"className":22898,"style":8875},[2282],[83,22900],{}," se acerca a 1, la pérdida se dispara a infinito (mala predicción).",[12,22903,22904],{},"La naturaleza logarítmica de la función es la que garantiza que el modelo sea penalizado severamente cuando se muestra \"seguro pero equivocado\", lo que obliga al modelo a ajustar sus pesos de forma más agresiva para mejorar las predicciones.",[32,22906,22908],{"id":22907},"validación-y-optimización","Validación y Optimización",[53,22910,22912],{"id":22911},"métricas-de-evaluación","Métricas de Evaluación",[12,22914,22915,22916,22918],{},"Para ",[40,22917,7106],{},", las métricas comunes incluyen:",[1359,22920,22921,22927,22933,22939],{},[1362,22922,22923,22926],{},[40,22924,22925],{},"Error Cuadrático Medio (MSE)",": Promedio de los cuadrados de las diferencias entre los valores reales y las predicciones.",[1362,22928,22929,22932],{},[40,22930,22931],{},"Error Raíz Cuadrático Medio (RMSE)",": Raíz cuadrada del MSE, que tiene la misma unidad que la variable dependiente.",[1362,22934,22935,22938],{},[40,22936,22937],{},"Coeficiente de Determinación (R²)",": Proporción de la varianza en la variable dependiente que es explicada por el modelo.",[1362,22940,22941,22944],{},[40,22942,22943],{},"Error Absoluto Medio (MAE)",": Promedio de las diferencias absolutas entre los valores reales y las predicciones.",[12,22946,22915,22947,22918],{},[40,22948,17511],{},[1359,22950,22951,22957,22963,22968],{},[1362,22952,22953,22956],{},[40,22954,22955],{},"Exactitud (Accuracy)",": Proporción de predicciones correctas sobre el total de ejemplos.",[1362,22958,22959,22962],{},[40,22960,22961],{},"Precisión (Precision)",": Proporción de verdaderos positivos sobre el total de predicciones positivas.",[1362,22964,22965,22967],{},[40,22966,5175],{},": Proporción de verdaderos positivos sobre el total de ejemplos reales positivos.",[1362,22969,22970,22973],{},[40,22971,22972],{},"F1 Score",": Media armónica de la precisión y el recall, que proporciona una medida equilibrada entre ambos.",[2073,22975,22976],{},[12,22977,22978],{},"La elección de la métrica adecuada depende del contexto del problema y de las consecuencias de los errores de clasificación. Por ejemplo, en un problema de detección de fraude, es más importante minimizar los falsos negativos (no detectar un fraude) que los falsos positivos (marcar una transacción legítima como fraude), por lo que el recall podría ser una métrica más relevante que la precisión.",[53,22980,22982],{"id":22981},"optimización","Optimización",[12,22984,22985,22986,22989],{},"La optimización de modelos de machine learning se refiere al proceso de ajustar los parámetros del modelo para ",[40,22987,22988],{},"minimizar la función de pérdida",". Esto se puede lograr mediante técnicas como el descenso de gradiente, que iterativamente ajusta los pesos del modelo en la dirección que reduce la pérdida.",[12,22991,22992],{},"El descenso de gradiente se puede expresar matemáticamente como:",[83,22994,22996],{"className":22995},[2147],[83,22997,22999,23034],{"className":22998},[2151],[83,23000,23002],{"className":23001},[2155],[2157,23003,23004],{"xmlns":2159,"display":2160},[2162,23005,23006,23031],{},[2165,23007,23008,23011,23013,23015,23017,23020,23023,23025,23027,23029],{},[2178,23009,23010],{},"θ",[2172,23012,229],{},[2178,23014,23010],{},[2172,23016,8650],{},[2178,23018,23019],{},"α",[2178,23021,23022],{"mathvariant":689},"∇",[2178,23024,21403],{},[2172,23026,187],{"stretchy":6169},[2178,23028,23010],{},[2172,23030,534],{"stretchy":6169},[2214,23032,23033],{"encoding":2216},"\\theta = \\theta - \\alpha \\nabla J(\\theta)",[83,23035,23037,23056,23074],{"className":23036,"ariaHidden":2204},[2221],[83,23038,23040,23043,23047,23050,23053],{"className":23039},[2225],[83,23041],{"className":23042,"style":2388},[2229],[83,23044,23010],{"className":23045,"style":23046},[2234,2264],"margin-right:0.0278em;",[83,23048],{"className":23049,"style":2243},[2242],[83,23051,229],{"className":23052},[2247],[83,23054],{"className":23055,"style":2243},[2242],[83,23057,23059,23062,23065,23068,23071],{"className":23058},[2225],[83,23060],{"className":23061,"style":2643},[2229],[83,23063,23010],{"className":23064,"style":23046},[2234,2264],[83,23066],{"className":23067,"style":2319},[2242],[83,23069,8650],{"className":23070},[2323],[83,23072],{"className":23073,"style":2319},[2242],[83,23075,23077,23080,23084,23087,23090,23093,23096],{"className":23076},[2225],[83,23078],{"className":23079,"style":6250},[2229],[83,23081,23019],{"className":23082,"style":23083},[2234,2264],"margin-right:0.0037em;",[83,23085,23022],{"className":23086},[2234],[83,23088,21403],{"className":23089,"style":21513},[2234,2264],[83,23091,187],{"className":23092},[6254],[83,23094,23010],{"className":23095,"style":23046},[2234,2264],[83,23097,534],{"className":23098},[6350],[12,23100,7598],{},[1359,23102,23103,23135,23167],{},[1362,23104,23105,23134],{},[83,23106,23108,23122],{"className":23107},[2151],[83,23109,23111],{"className":23110},[2155],[2157,23112,23113],{"xmlns":2159},[2162,23114,23115,23119],{},[2165,23116,23117],{},[2178,23118,23010],{},[2214,23120,23121],{"encoding":2216},"\\theta",[83,23123,23125],{"className":23124,"ariaHidden":2204},[2221],[83,23126,23128,23131],{"className":23127},[2225],[83,23129],{"className":23130,"style":2388},[2229],[83,23132,23010],{"className":23133,"style":23046},[2234,2264]," representa los parámetros del modelo (por ejemplo, los coeficientes en regresión).",[1362,23136,23137,23166],{},[83,23138,23140,23154],{"className":23139},[2151],[83,23141,23143],{"className":23142},[2155],[2157,23144,23145],{"xmlns":2159},[2162,23146,23147,23151],{},[2165,23148,23149],{},[2178,23150,23019],{},[2214,23152,23153],{"encoding":2216},"\\alpha",[83,23155,23157],{"className":23156,"ariaHidden":2204},[2221],[83,23158,23160,23163],{"className":23159},[2225],[83,23161],{"className":23162,"style":7592},[2229],[83,23164,23019],{"className":23165,"style":23083},[2234,2264]," es la tasa de aprendizaje, que controla el tamaño de los pasos que se dan en cada iteración.",[1362,23168,23169,23218],{},[83,23170,23172,23194],{"className":23171},[2151],[83,23173,23175],{"className":23174},[2155],[2157,23176,23177],{"xmlns":2159},[2162,23178,23179,23191],{},[2165,23180,23181,23183,23185,23187,23189],{},[2178,23182,23022],{"mathvariant":689},[2178,23184,21403],{},[2172,23186,187],{"stretchy":6169},[2178,23188,23010],{},[2172,23190,534],{"stretchy":6169},[2214,23192,23193],{"encoding":2216},"\\nabla J(\\theta)",[83,23195,23197],{"className":23196,"ariaHidden":2204},[2221],[83,23198,23200,23203,23206,23209,23212,23215],{"className":23199},[2225],[83,23201],{"className":23202,"style":6250},[2229],[83,23204,23022],{"className":23205},[2234],[83,23207,21403],{"className":23208,"style":21513},[2234,2264],[83,23210,187],{"className":23211},[6254],[83,23213,23010],{"className":23214,"style":23046},[2234,2264],[83,23216,534],{"className":23217},[6350]," es el gradiente de la función de pérdida con respecto a los parámetros, que indica la dirección de mayor aumento de la pérdida.",[12,23220,23221],{},"El proceso de optimización continúa hasta que se alcanza un criterio de convergencia, como un número máximo de iteraciones o una mejora mínima en la función de pérdida.",[1359,23223,23224,23260,23314],{},[1362,23225,23226,23227,23230,23231,23259],{},"Posee una ",[40,23228,23229],{},"tasa de aprendizaje"," (",[83,23232,23234,23247],{"className":23233},[2151],[83,23235,23237],{"className":23236},[2155],[2157,23238,23239],{"xmlns":2159},[2162,23240,23241,23245],{},[2165,23242,23243],{},[2178,23244,23019],{},[2214,23246,23153],{"encoding":2216},[83,23248,23250],{"className":23249,"ariaHidden":2204},[2221],[83,23251,23253,23256],{"className":23252},[2225],[83,23254],{"className":23255,"style":7592},[2229],[83,23257,23019],{"className":23258,"style":23083},[2234,2264],") que controla el tamaño de los pasos que se dan en cada iteración (típicamente un valor pequeño como 0.01 o 0.001).",[1362,23261,8285,23262,23230,23265,23313],{},[40,23263,23264],{},"gradiente",[83,23266,23268,23289],{"className":23267},[2151],[83,23269,23271],{"className":23270},[2155],[2157,23272,23273],{"xmlns":2159},[2162,23274,23275,23287],{},[2165,23276,23277,23279,23281,23283,23285],{},[2178,23278,23022],{"mathvariant":689},[2178,23280,21403],{},[2172,23282,187],{"stretchy":6169},[2178,23284,23010],{},[2172,23286,534],{"stretchy":6169},[2214,23288,23193],{"encoding":2216},[83,23290,23292],{"className":23291,"ariaHidden":2204},[2221],[83,23293,23295,23298,23301,23304,23307,23310],{"className":23294},[2225],[83,23296],{"className":23297,"style":6250},[2229],[83,23299,23022],{"className":23300},[2234],[83,23302,21403],{"className":23303,"style":21513},[2234,2264],[83,23305,187],{"className":23306},[6254],[83,23308,23010],{"className":23309,"style":23046},[2234,2264],[83,23311,534],{"className":23312},[6350],") es un vector que contiene las derivadas parciales de la función de pérdida con respecto a cada parámetro, indicando la dirección de mayor aumento de la pérdida.",[1362,23315,23316,23317,23320],{},"El proceso de optimización continúa hasta que se alcanza un criterio de ",[40,23318,23319],{},"convergencia",", como un número máximo de iteraciones o una mejora mínima en la función de pérdida.",[12,23322,23323],{},"Gráficamente:",[12,23325,23326,23330],{},[1882,23327],{"alt":23328,"src":23329},"Gráfico del proceso de optimización con descenso de gradiente","\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations\u002Fshared\u002Fgradient-descent.webp",[1887,23331,23332],{},"Optimización con Descenso de Gradiente",[1406,23334,23335,23338,23341,23344],{},[1362,23336,23337],{},"Se inicia con un punto aleatorio en la función de pérdida (INITIAL POINT).",[1362,23339,23340],{},"Se calcula el gradiente en ese punto, que indica la dirección de mayor aumento de la pérdida.",[1362,23342,23343],{},"Se actualizan los parámetros del modelo en la dirección opuesta al gradiente, con un paso controlado por la tasa de aprendizaje (LEARNING RATE \u002F STEP SIZE).",[1362,23345,23346],{},"Este proceso se repite iterativamente hasta que se alcanza un mínimo local o global de la función de pérdida, lo que indica que el modelo ha sido optimizado.",[12,23348,23349],{},"La tasa de aprendizaje es crucial para el éxito del proceso de optimización:",[1359,23351,23352,23362,23371],{},[1362,23353,23354,23357,23358,23361],{},[40,23355,23356],{},"DIVERGENCIA",": Si la tasa de aprendizaje es demasiado ",[40,23359,23360],{},"alta",", el modelo puede divergir, saltando por encima del mínimo y aumentando la pérdida.",[1362,23363,23364,23357,23367,23370],{},[40,23365,23366],{},"CONVERGENCIA LENTA",[40,23368,23369],{},"baja",", el proceso de optimización puede ser muy lento, tardando mucho tiempo en converger o quedándose atrapado en un mínimo local.",[1362,23372,23373,23376],{},[40,23374,23375],{},"CONVERGENCIA ÓPTIMA",": Una tasa de aprendizaje adecuada permite que el modelo converja de manera eficiente hacia un mínimo global o local, optimizando la función de pérdida de manera efectiva.",[32,23378,23380],{"id":23379},"el-proceso-de-machine-learning","El Proceso de Machine Learning",[12,23382,23383],{},"Podemos resumir el proceso de ML en:",[1406,23385,23386,23397,23408,23419,23429],{},[1362,23387,23388,23391,23392],{},[40,23389,23390],{},"Paradigma de aprendizaje",": Elegir el tipo de aprendizaje (supervisado, no supervisado, por refuerzo) según el problema a resolver.\n",[1359,23393,23394],{},[1362,23395,23396],{},"Define el tipo de problema y datos disponibles.",[1362,23398,23399,23402,23403],{},[40,23400,23401],{},"Modelo matemático",": Seleccionar un modelo adecuado (regresión, clasificación, clustering) y entender su formulación matemática.\n",[1359,23404,23405],{},[1362,23406,23407],{},"Establece la relación matemática entre entrada y salida.",[1362,23409,23410,23413,23414],{},[40,23411,23412],{},"Función de pérdida\u002Fcosto",": Definir una función de pérdida que mida el error del modelo y que se pueda optimizar.\n",[1359,23415,23416],{},[1362,23417,23418],{},"Cuántifica que tan malo es el modelo en sus predicciones.",[1362,23420,23421,23423,23424],{},[40,23422,22982],{},": Utilizar técnicas como el descenso de gradiente para ajustar los parámetros del modelo y minimizar la función de pérdida.\n",[1359,23425,23426],{},[1362,23427,23428],{},"Encuentra los mejores parámetros para que el modelo haga buenas predicciones.",[1362,23430,23431,23433,23434],{},[40,23432,5871],{},": Medir el rendimiento del modelo utilizando métricas adecuadas para el tipo de problema (MSE para regresión, precisión\u002Frecall para clasificación, etc.).\n",[1359,23435,23436],{},[1362,23437,23438],{},"Valida el desempeño del modelo y su capacidad de generalización a datos no vistos.",{"title":79,"searchDepth":116,"depth":116,"links":23440},[23441,23446,23450,23454],{"id":6120,"depth":103,"text":6121,"children":23442},[23443,23444,23445],{"id":6147,"depth":116,"text":6148},{"id":6815,"depth":116,"text":6816},{"id":7049,"depth":116,"text":7050},{"id":7092,"depth":103,"text":7093,"children":23447},[23448,23449],{"id":7106,"depth":116,"text":6801},{"id":17511,"depth":116,"text":6795},{"id":22907,"depth":103,"text":22908,"children":23451},[23452,23453],{"id":22911,"depth":116,"text":22912},{"id":22981,"depth":116,"text":22982},{"id":23379,"depth":103,"text":23380},"2026-04-06","\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations\u002Fshared\u002Fml-paradigms.webp",{},"\u002Fblog\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations",{"title":4418,"description":6106},{"loc":23461,"priority":4394,"lastmod":23455},"\u002Fes\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations","machine-learning-paradigms-and-mathematical-foundations","blog\u002Fblog\u002Fmachine-learning-paradigms-and-mathematical-foundations","Tipos de aprendizaje automático, algoritmos comunes y fundamentos matemáticos esenciales para entender cómo funcionan los modelos de machine learning.",[6095,23466,23467],"Inteligencia Artificial","Matemáticas para Machine Learning","tlDDlQKGAvkZ6PPf-z3-0xGqmpAfXOOwFkPCGfv5gS8",{"id":23470,"title":6113,"author":7,"body":23471,"date":24104,"description":23475,"extension":4387,"image":24105,"lastmod":24104,"meta":24106,"navigation":160,"order":103,"path":24107,"seo":24108,"sitemap":24109,"slug":24111,"stem":24112,"summary":24113,"tags":24114,"__hash__":24116},"content_es\u002Fblog\u002Fblog\u002Fmachine-learning-fundamentals.md",{"type":9,"value":23472,"toc":24095},[23473,23476,23478,23480,23484,23500,23503,23527,23530,23544,23546,23550,23553,23621,23623,23627,23630,23741,23743,23847,23849,23893,23913,23915,23919,23922,23976,23980,23983,23992,23995,24006,24019,24021,24025,24051,24061,24063,24067,24070,24090,24092],[12,23474,23475],{},"Esta es la primera parte de una serie de artículos donde exploraremos el aprendizaje automático, desde sus conceptos básicos hasta redes neuronales y la creación de un modelo de machine learning. En esta primera parte, nos centraremos en los fundamentos del aprendizaje automático, incluyendo qué es, sus tipos y algunos algoritmos comunes.",[26,23477],{},[29,23479],{},[32,23481,23483],{"id":23482},"inteligencia-artificial-y-machine-learning","Inteligencia Artificial y Machine Learning",[12,23485,23486,23487,4944,23490,1966,23493,23496,23497,133],{},"Te despiertas un día, abres Netflix y te encuentras recomendada exactamente la serie que querías ver. Luego, abres Google escribes algo y el buscador completa tu frase antes de que termines de teclear. ¿Cómo hacen esto? La respuesta es: Inteligencia Artificial. La IA, es una disciplina enfocada en desarrollar sistemas capaces de realizar tareas que normalmente requieren inteligencia humana, como ",[40,23488,23489],{},"aprender",[40,23491,23492],{},"razonar",[40,23494,23495],{},"percibir"," nuestro entorno, asi como ",[40,23498,23499],{},"tomar decisiones",[12,23501,23502],{},"Existen tres tipos de IA:",[1359,23504,23505,23511,23517],{},[1362,23506,23507,23510],{},[40,23508,23509],{},"IA débil o estrecha (Artificial Narrow Intelligence o ANI)",": Es la IA que tenemos hoy en día. Está diseñada para realizar tareas específicas, como reconocimiento de voz, recomendaciones de productos o traducción automática. No tiene conciencia ni comprensión real, simplemente sigue algoritmos y patrones predefinidos. Los LLM como GPT, Claude o Gemini, son ejemplos de IA débil, ya que están diseñados para procesar y generar texto, \"solamente\" son modelos estadisticos que predicen texto, y  no tienen una comprensión profunda del mundo ni pueden realizar tareas fuera de su ámbito específico. Aunque parecen inteligentes, en realidad solo están imitando patrones de lenguaje basados en los datos con los que fueron entrenados.",[1362,23512,23513,23516],{},[40,23514,23515],{},"IA general (Artifical General Intelligence o AGI)",": Es una IA hipotética que tendría la capacidad de entender, aprender y aplicar conocimientos en una amplia variedad de tareas, similar a la inteligencia humana. Aún no existe, pero es un objetivo a largo plazo en el campo de la IA.",[1362,23518,23519,23522,23523,23526],{},[40,23520,23521],{},"IA superinteligente (Artificial Superintelligence o ASI)",": Es una IA que superaría la inteligencia humana en todos los aspectos, incluyendo creatividad, resolución de problemas y toma de decisiones. Es un concepto ",[40,23524,23525],{},"teórico"," que plantea muchas preguntas éticas y filosóficas sobre el futuro de la humanidad.",[12,23528,23529],{},"¿Dónde entra el Machine Learning? Es muy común confundir la IA con el Machine Learning, pero no son exactamente lo mismo. Podemos decir que la Inteligencia Artificial es un gran paraguas conceptual, y debajo de ese paraguas se encuentra el Machine Learning, un subcampo específico que permite a las computadoras aprender automáticamente a partir de datos, sin necesidad de que un humano las programe paso a paso.",[2073,23531,23532,23535],{},[12,23533,23534],{},"Recursos recomendados:",[1359,23536,23537],{},[1362,23538,23539],{},[19,23540,23543],{"href":23541,"rel":23542},"https:\u002F\u002Fyoutu.be\u002FdKqwnCKrpVI?si=g6qqFa_1G_M5P3LS",[23],"Inteligencia Artificial vs Machine Learning vs Deep Learning | Machine Learning 101",[29,23545],{},[32,23547,23549],{"id":23548},"subcampos-de-la-ia","Subcampos de la IA",[12,23551,23552],{},"Dentro del gran paraguas de la IA, hay varios subcampos que se especializan en diferentes aspectos de la inteligencia artificial:",[1359,23554,23555,23561,23567,23573,23579,23585,23591,23597,23603,23609,23615],{},[1362,23556,23557,23560],{},[40,23558,23559],{},"Aprendizaje Automático (Machine Learning)",": Se centra en desarrollar algoritmos que permiten a las máquinas aprender de los datos y mejorar su rendimiento con el tiempo sin ser explícitamente programadas para cada tarea específica.",[1362,23562,23563,23566],{},[40,23564,23565],{},"Aprendizaje Profundo (Deep Learning)",": Es una rama del aprendizaje automático que utiliza redes neuronales profundas para modelar y resolver problemas complejos. Es especialmente efectivo en tareas como reconocimiento de voz, visión por computadora y procesamiento del lenguaje natural.",[1362,23568,23569,23572],{},[40,23570,23571],{},"Procesamiento del Lenguaje Natural (Natural Language Processing o NLP)",": Se enfoca en la interacción entre las computadoras y el lenguaje humano, permitiendo a las máquinas entender, interpretar y generar texto de manera natural. Es lo que hace posible que los chatbots como ChatGPT puedan mantener conversaciones coherentes con los usuarios.",[1362,23574,23575,23578],{},[40,23576,23577],{},"Visión por Computadora (Computer Vision)",": Se ocupa de permitir que las máquinas comprendan y procesen imágenes y videos. Esto es fundamental para aplicaciones como el reconocimiento facial, la conducción autónoma y la detección de objetos.",[1362,23580,23581,23584],{},[40,23582,23583],{},"Robótica",": Se dedica al diseño y construcción de robots que pueden realizar tareas físicas en el mundo real, desde la fabricación hasta la asistencia médica.",[1362,23586,23587,23590],{},[40,23588,23589],{},"Sistemas Expertos",": Son programas que imitan la toma de decisiones de un experto humano en un dominio específico, utilizando reglas y lógica para resolver problemas complejos.",[1362,23592,23593,23596],{},[40,23594,23595],{},"Razonamiento Automático",": Se enfoca en inferir conclusiones lógicas a partir de reglas formales, no es lo mismo que el aprendizaje automático, este campo incluye lógica simbólica, resolución de problemas y planificación automática.",[1362,23598,23599,23602],{},[40,23600,23601],{},"Agentes Inteligentes",": Son sistemas que pueden percibir su entorno, razonar sobre él y tomar decisiones para alcanzar objetivos específicos. Pueden ser tan simples como un chatbot o tan complejos como un sistema de conducción autónoma (puede usar ML, reglas simples, razonamiento lógico, etc).",[1362,23604,23605,23608],{},[40,23606,23607],{},"IA Distribuida",": Se refiere a sistemas de IA que operan en múltiples dispositivos o nodos, colaborando para resolver problemas de manera más eficiente. Esto es especialmente relevante en aplicaciones como el Internet de las Cosas (IoT) y la computación en la nube.",[1362,23610,23611,23614],{},[40,23612,23613],{},"IA Explicable (XAI)",": Se centra en desarrollar modelos de IA que sean transparentes y comprensibles para los humanos, permitiendo a los usuarios entender cómo y por qué la IA toma ciertas decisiones.",[1362,23616,23617,23620],{},[40,23618,23619],{},"Ética y Gobernanza de la IA",": Se ocupa de las implicaciones éticas, legales y sociales del desarrollo y uso de la IA, abordando temas como la privacidad, la equidad, la transparencia.",[29,23622],{},[32,23624,23626],{"id":23625},"como-aprende-una-máquina","Como aprende una máquina",[12,23628,23629],{},"Todo depende de los datos que le demos:",[1359,23631,23632],{},[1362,23633,23634,23636,23637,23640,23641,23644,23645,23647,23648,23696,23698,23699,23701,23702,23714,23716,23717,23723,23724,23726,23727],{},[40,23635,6148],{},": Aquí le damos a la máquina ejemplos claros con las respuestas correctas ya \"etiquetadas\". Por ejemplo, si queremos que la IA ayude en un diagnóstico médico, le damos miles de historiales médicos donde ya sabemos qué paciente estaba ",[40,23638,23639],{},"enfermo"," y qué paciente estaba ",[40,23642,23643],{},"sano",".\nLa máquina aprende a reconocer patrones en esos datos para poder predecir el diagnóstico de nuevos pacientes basándose en lo que ha aprendido.",[2903,23646],{},"Un ejemplo sencillo sería algo así:",[3070,23649,23650,23666],{},[3073,23651,23652],{},[3076,23653,23654,23657,23660,23663],{},[3079,23655,23656],{},"Edad",[3079,23658,23659],{},"Síntomas",[3079,23661,23662],{},"Resultado de Pruebas",[3079,23664,23665],{},"Diagnóstico",[3086,23667,23668,23682],{},[3076,23669,23670,23673,23676,23679],{},[3091,23671,23672],{},"45",[3091,23674,23675],{},"Fiebre, Tos",[3091,23677,23678],{},"Positivo",[3091,23680,23681],{},"Enfermo",[3076,23683,23684,23687,23690,23693],{},[3091,23685,23686],{},"30",[3091,23688,23689],{},"Dolor de cabeza",[3091,23691,23692],{},"Negativo",[3091,23694,23695],{},"Sano",[2903,23697],{},"La etiqueta aquí es el \"Diagnóstico\", y la máquina aprende a asociar las características (Edad, Síntomas, Resultado de Pruebas) con esa etiqueta para hacer predicciones futuras.",[2903,23700],{},"Dentro del aprendizaje supervisado, hay dos tipos principales de tareas:",[1359,23703,23704,23709],{},[1362,23705,23706,23708],{},[40,23707,6795],{},": Donde la máquina asigna una etiqueta a cada ejemplo. Como clasificar correos electrónicos como \"spam\" o \"no spam\".",[1362,23710,23711,23713],{},[40,23712,6801],{},": Donde la máquina predice un valor continuo. Por ejemplo, predecir el precio de una casa basándose en características como el tamaño, la ubicación y el número de habitaciones.",[2903,23715],{},"Basicamente si la respuesta que queremos predecir es una categoría (o una ",[19,23718,23722],{"href":23719,"target":17502,"rel":23720,"ariaLabel":23721},"https:\u002F\u002Fwww.probabilidadyestadistica.net\u002Fvariable-discreta",[17504,17505],"LinkedIn","variable discreta","), es clasificación, si la respuesta representa una cantidad medible en una escala continua, es regresión.\nY el requisito para que el aprendizaje supervisado funcione bien es tener un conjunto de datos grande y representativo, con etiquetas precisas. Si los datos son escasos o las etiquetas son incorrectas, la máquina no podrá aprender correctamente y sus predicciones serán inexactas.",[2903,23725],{},"Ejemplos de aplicaciones de ML son:",[1359,23728,23729,23732,23735,23738],{},[1362,23730,23731],{},"Detección de fraudes en transacciones financieras (clasificación)",[1362,23733,23734],{},"Predicción de precios de acciones (regresión)",[1362,23736,23737],{},"Reconocimiento de imágenes (clasificación)",[1362,23739,23740],{},"Análisis de sentimientos en redes sociales (clasificación)",[29,23742],{},[1359,23744,23745],{},[1362,23746,23747,23749,23750,23752,23753,23792,23794,23795,23844,23846],{},[40,23748,6816],{},": Imagina que te sueltan en un país desconocido y tienes que deducir cómo funciona la sociedad solo observando, es algo similar. Aquí, la máquina recibe datos sin etiquetas y debe encontrar patrones ocultos por sí sola. El sistema tendrá que analizar similitudes, diferencias y comportamientos para encontrar agrupaciones o patrones inusuales. No hay un \"profesor\" que le diga si está bien o mal.",[2903,23751],{},"Técnicas principales:",[1406,23754,23755,23772,23786],{},[1362,23756,23757,23760,23761],{},[40,23758,23759],{},"Clustering (Agrupamiento)",": Agrupa datos similares entre si.\nSe usa típicamente para segmentación de clientes, agrupar documentos por tema y organización automática de imágenes, etc. Algunos algoritmos:\n",[1359,23762,23763,23766,23769],{},[1362,23764,23765],{},"K-means clustering",[1362,23767,23768],{},"DBSCAN",[1362,23770,23771],{},"Hierarchical clustering",[1362,23773,23774,23777,23778],{},[40,23775,23776],{},"Reducción de dimensionalidad",": Este busca reducir la cantidad de variables manteniendo la información importante. Usado para visualizar datos complejos y preparar datos para otros modelos.\n",[1359,23779,23780,23783],{},[1362,23781,23782],{},"Principal Component Analysis (PCA)",[1362,23784,23785],{},"t-SNE",[1362,23787,23788,23791],{},[40,23789,23790],{},"Detección de anomalías",": Identifica datos que se comportan diferente del resto. Útil para detectar fraudes, fallos en sistemas y comportamientos sospechosos.",[2903,23793],{},"Un ejemplo sencillo sería:",[3070,23796,23797,23809],{},[3073,23798,23799],{},[3076,23800,23801,23803,23806],{},[3079,23802,23656],{},[3079,23804,23805],{},"Ingresos Anuales",[3079,23807,23808],{},"Gastos Mensuales",[3086,23810,23811,23822,23833],{},[3076,23812,23813,23816,23819],{},[3091,23814,23815],{},"25",[3091,23817,23818],{},"$30,000",[3091,23820,23821],{},"$1,000",[3076,23823,23824,23827,23830],{},[3091,23825,23826],{},"40",[3091,23828,23829],{},"$80,000",[3091,23831,23832],{},"$3,000",[3076,23834,23835,23838,23841],{},[3091,23836,23837],{},"60",[3091,23839,23840],{},"$50,000",[3091,23842,23843],{},"$2,000",[2903,23845],{},"La máquina podría agrupar a los clientes en segmentos basados en sus ingresos y gastos, sin que le digamos explícitamente qué grupos existen.\nCon esto podemos identificar patrones de consumo, como por ejemplo, que los clientes jóvenes tienden a gastar menos que los clientes de mediana edad, o que hay un grupo de clientes con ingresos altos pero gastos bajos, lo que podría indicar un segmento de ahorro.",[29,23848],{},[1359,23850,23851],{},[1362,23852,23853,23855,23856,133,23861,23863,23864,23886,23888,23889],{},[40,23854,7050],{},": Piensa en cómo entrenas a una mascota con premios. La máquina (el agente) toma decisiones en un entorno y recibe \"recompensas\" o \"penalizaciones\". Así es como los sistemas de conducción autónoma de Tesla o los robots aprenden a navegar por el mundo físico. Un ejemplo que me gusta es el de un video donde ",[19,23857,23860],{"href":23858,"target":17502,"rel":23859},"https:\u002F\u002Fyoutu.be\u002FPKDMGPf-PEA?si=tAEMO3cETdPrvi_t",[17504,17505],"entrenan a un agente para jugar Geometry Dash",[2903,23862],{},"En este tipo de aprendizaje se tienen cuatro componentes principales:",[1406,23865,23866,23871,23876,23881],{},[1362,23867,23868,23870],{},[40,23869,7060],{},": Es el sistema que toma decisiones y aprende a través de la interacción con el entorno. Puede ser un robot, un programa de computadora o cualquier sistema que pueda percibir su entorno y actuar sobre él.",[1362,23872,23873,23875],{},[40,23874,7066],{},": Es el mundo en el que el agente opera. Puede ser un entorno físico, como un robot en una habitación, o un entorno virtual, como un videojuego.",[1362,23877,23878,23880],{},[40,23879,7072],{},": Es la señal que el agente recibe después de tomar una acción. Puede ser positiva (recompensa) o negativa (penalización) y sirve para guiar el aprendizaje del agente.",[1362,23882,23883,23885],{},[40,23884,7078],{},": Es la estrategia que el agente utiliza para decidir qué acción tomar en función de su estado actual y de las recompensas que ha recibido en el pasado.",[2903,23887],{},"Básicamente siguen un flujo como el siguiente:",[23890,23891],"mermaid-diagram",{"content":23892},"graph TD\n A[Agente] -->|Toma acción| B(Entorno)\n B -->|Proporciona recompensa| C[Recompensa]\n C -->|Actualiza política| A",[2073,23894,23895,23897],{},[12,23896,23534],{},[1359,23898,23899,23906],{},[1362,23900,23901],{},[19,23902,23905],{"href":23903,"rel":23904},"https:\u002F\u002Fyoutu.be\u002FoT3arRRB2Cw?si=ykU9KQjQLxdn9ggj",[23],"¿Qué es el Aprendizaje Supervisado y No Supervisado? | DotCSV",[1362,23907,23908],{},[19,23909,23912],{"href":23910,"rel":23911},"https:\u002F\u002Fyoutu.be\u002FqBtB-xcJp4c?si=c2GuJBCFPorKGN44",[23],"El APRENDIZAJE POR REFUERZO: la guía DEFINITIVA",[29,23914],{},[32,23916,23918],{"id":23917},"pipeline-de-un-proyecto-de-ia","Pipeline de un proyecto de IA",[12,23920,23921],{},"Un proyecto de IA generalmente sigue un proceso estructurado que incluye varias etapas clave:",[1406,23923,23924,23929,23935,23941,23947,23953,23959,23965,23970],{},[1362,23925,23926,23928],{},[40,23927,5524],{},": Es fundamental entender claramente el problema que se quiere resolver y los objetivos del proyecto. Esto incluye identificar las preguntas que se quieren responder, los resultados esperados y las métricas de éxito.",[1362,23930,23931,23934],{},[40,23932,23933],{},"Recolección de datos",": Se recopilan los datos necesarios para entrenar el modelo de IA. Esto puede incluir datos estructurados (como bases de datos) o no estructurados (como texto, imágenes o videos). Es importante asegurarse de que los datos sean de alta calidad y representativos del problema que se quiere resolver.",[1362,23936,23937,23940],{},[40,23938,23939],{},"Preprocesamiento de datos",": Los datos recopilados a menudo necesitan ser limpiados y transformados antes de ser utilizados para entrenar el modelo. Esto puede incluir la eliminación de valores faltantes, la normalización de datos, la codificación de variables categóricas y la división de los datos en conjuntos de entrenamiento y prueba.",[1362,23942,23943,23946],{},[40,23944,23945],{},"Selección del modelo",": Se elige el algoritmo de aprendizaje automático más adecuado para el problema en cuestión. Esto puede depender de la naturaleza de los datos, la complejidad del problema y los recursos disponibles.",[1362,23948,23949,23952],{},[40,23950,23951],{},"Entrenamiento del modelo",": Se utiliza el conjunto de datos de entrenamiento para entrenar el modelo de IA. Durante esta etapa, el modelo aprende a partir de los datos y ajusta sus parámetros para minimizar el error en las predicciones.",[1362,23954,23955,23958],{},[40,23956,23957],{},"Evaluación del modelo",": Se evalúa el rendimiento del modelo utilizando el conjunto de prueba. Se utilizan métricas específicas para medir la precisión, la exactitud, la sensibilidad y otras características del modelo, dependiendo del tipo de problema (clasificación, regresión, etc.).",[1362,23960,23961,23964],{},[40,23962,23963],{},"Ajuste de hiperparámetros",": Si el rendimiento del modelo no es satisfactorio, se pueden ajustar los hiperparámetros del modelo para mejorar su rendimiento. Esto puede incluir cambiar la arquitectura del modelo, ajustar la tasa de aprendizaje o modificar otros parámetros específicos del algoritmo.",[1362,23966,23967,23969],{},[40,23968,5948],{},": Una vez que el modelo ha sido entrenado y evaluado, se implementa en un entorno de producción donde puede ser utilizado para hacer predicciones en tiempo real o procesar nuevos datos.",[1362,23971,23972,23975],{},[40,23973,23974],{},"Mantenimiento y actualización",": Después de la implementación, es importante monitorear el rendimiento del modelo y actualizarlo regularmente para asegurarse de que siga siendo efectivo a medida que cambian los datos y las condiciones del entorno.",[32,23977,23979],{"id":23978},"memorizar-vs-aprender","Memorizar vs Aprender",[12,23981,23982],{},"Cuando hablamos de aprendizaje, ya sea humano o de máquinas, existe un concepto crucial que debemos entender: memorizar no es lo mismo que aprender.",[12,23984,23985,23988,23989,23991],{},[40,23986,23987],{},"Memorizar"," es como copiar y pegar información sin realmente entenderla. Por ejemplo, si memorizas la fórmula del área de un círculo (A = πr²) sin comprender qué significa cada parte, no podrás aplicarla correctamente en diferentes contextos. La memoria te salva en lo inmediato, pero no te da la capacidad de adaptarte a nuevas situaciones o resolver problemas que no has visto antes, en cambio, ",[40,23990,23489],{}," implica comprender los conceptos que están detrás y ser capaz de aplicarlos en situaciones nuevas.",[12,23993,23994],{},"En el mundo del aprendizaje automático, una máquina que solo memoriza los datos de entrenamiento puede tener un rendimiento excelente en esos datos específicos, pero luego fallar estrepitosamente cuando se utiliza en entornos reales. Por eso, en machine learning, el verdadero objetivo no es memorizar patrones específicos, sino generalizar: aprender reglas y relaciones que funcionen más allá de los ejemplos vistos.",[12,23996,23997,23998,24001,24002,24005],{},"Pero aprender tampoco es sencillo, a veces, las máquinas sufren de ",[40,23999,24000],{},"Overfitting"," (sobreajuste), que ocurre cuando un modelo \"memoriza\" los datos de entrenamiento a la perfección, pero fracasa rotundamente cuando se enfrenta a datos nuevos en el mundo real. Es exactamente igual que un estudiante que memoriza las respuestas de un examen sin entender realmente los conceptos. Por el contrario, si el modelo es demasiado simple y no aprende nada, sufre de ",[40,24003,24004],{},"Underfitting"," (subajuste), como un estudiante que no estudió lo suficiente.",[2073,24007,24008,24010],{},[12,24009,23534],{},[1359,24011,24012],{},[1362,24013,24014],{},[19,24015,24018],{"href":24016,"rel":24017},"https:\u002F\u002Fyoutu.be\u002Fo3DztvnfAJg?si=lorMlPZqLAMa-EV3",[23],"Subajuste y sobreajuste: explicados",[29,24020],{},[32,24022,24024],{"id":24023},"los-componentes-de-un-sistema-de-ia","Los componentes de un sistema de IA",[1359,24026,24027,24039,24045],{},[1362,24028,24029,24032,24033,24038],{},[40,24030,24031],{},"Datos",": Son la base de cualquier sistema de IA. Sin datos, no hay aprendizaje. Deben ser de alta calidad, relevantes y representativos del problema que se quiere resolver. Con un alto volumen y con el menor ",[19,24034,24037],{"href":24035,"target":17502,"rel":24036},"https:\u002F\u002Fwww.innovatiana.com\u002Fes\u002Fpost\u002Fbias-estimation-in-machine-learning",[17504,17505],"sesgo"," posible.",[1362,24040,24041,24044],{},[40,24042,24043],{},"Algoritmos",": Son las recetas que la máquina sigue para aprender de los datos. Hay muchos tipos de algoritmos, cada uno con sus propias fortalezas y debilidades, y deben ser seleccionados cuidadosamente según el problema específico que se quiere resolver, configurados y ajustados para obtener el mejor rendimiento posible.",[1362,24046,24047,24050],{},[40,24048,24049],{},"Infraestructura",": Es el hardware y software necesario para procesar los datos y ejecutar los algoritmos. Esto incluye desde servidores (CPU, GPU, TPU) hasta plataformas de computación en la nube y herramientas de desarrollo (AWS, Azure, GCP), asi como almacenamiento de datos y sistemas de gestión de bases de datos.",[12,24052,24053,24054,24056,24057,24060],{},"A parte de estos componentes, tenemos la ",[40,24055,5870],{},", que es el proceso de medir el rendimiento del modelo de IA para asegurarse de que está funcionando correctamente y cumpliendo con los objetivos establecidos, asi como el rol de la ",[40,24058,24059],{},"ética y gobernanza",", que es fundamental para considerar las implicaciones éticas y sociales.",[29,24062],{},[32,24064,24066],{"id":24065},"la-ética-en-la-ia","La ética en la IA",[12,24068,24069],{},"A medida que la inteligencia artificial se vuelve más omnipresente en nuestras vidas, es crucial considerar las implicaciones éticas de su uso. Los modelos de machine learning pueden perpetuar sesgos existentes en los datos, lo que puede llevar a decisiones injustas o discriminatorias. Por ejemplo, si un modelo de contratación se entrena con datos históricos que reflejan prejuicios de género o raza, es probable que el modelo reproduzca esos sesgos en sus recomendaciones. Además, la privacidad de los datos es una preocupación importante. Es fundamental asegurarse de que los datos utilizados se recopilen y manejen de manera ética, respetando la privacidad y los derechos de las personas.",[1359,24071,24072,24078,24084],{},[1362,24073,24074,24077],{},[40,24075,24076],{},"Transparencia",": Los sistemas deben ser comprensibles y auditables para que los usuarios puedan entender cómo funcionan y por qué toman ciertas decisiones, una solución a esto es la IA explicable (XAI).",[1362,24079,24080,24083],{},[40,24081,24082],{},"Explicabilidad",": Los modelos de IA deben ser capaces de explicar sus decisiones de manera clara y comprensible para los usuarios, lo que ayuda a generar confianza y permite a los usuarios entender las razones detrás de las recomendaciones o acciones del sistema.",[1362,24085,24086,24089],{},[40,24087,24088],{},"Responsabilidad",": Se debe establecer claramente quién es responsable de las decisiones tomadas por los sistemas de IA, especialmente en casos donde las decisiones pueden tener un impacto significativo en la vida de las personas. Aqui entran en juego los marcos legales y regulaciones que deben ser desarrollados para garantizar que las empresas y desarrolladores de IA sean responsables de sus creaciones.",[29,24091],{},[12,24093,24094],{},"Hasta aquí la primera parte de esta serie de artículos sobre aprendizaje automático. En la próxima parte, exploraremos algunos paradigmas de machine learning y ciertos fundamentos matemáticos que son esenciales para entender cómo funcionan los algoritmos.",{"title":79,"searchDepth":116,"depth":116,"links":24096},[24097,24098,24099,24100,24101,24102,24103],{"id":23482,"depth":103,"text":23483},{"id":23548,"depth":103,"text":23549},{"id":23625,"depth":103,"text":23626},{"id":23917,"depth":103,"text":23918},{"id":23978,"depth":103,"text":23979},{"id":24023,"depth":103,"text":24024},{"id":24065,"depth":103,"text":24066},"2026-03-30","\u002Fblog\u002Fmachine-learning-fundamentals\u002Fshared\u002Fml-fundamentals.webp",{},"\u002Fblog\u002Fblog\u002Fmachine-learning-fundamentals",{"title":6113,"description":23475},{"loc":24110,"priority":4394,"lastmod":24104},"\u002Fes\u002Fblog\u002Fmachine-learning-fundamentals","machine-learning-fundamentals","blog\u002Fblog\u002Fmachine-learning-fundamentals","Conceptos básicos para iniciar en el mundo del aprendizaje automático",[24115,23466,4658,6096,6095],"Aprendizaje Automático","2v7h55fkUsJvxoYBntWpvJgjaGB1GovQylDStwlp07E",{"id":24118,"title":24119,"author":7,"body":24120,"date":30563,"description":24124,"extension":4387,"image":30564,"lastmod":30565,"meta":30566,"navigation":160,"order":86,"path":30567,"seo":30568,"sitemap":30569,"slug":30571,"stem":30572,"summary":30573,"tags":30574,"__hash__":30578},"content_es\u002Fblog\u002Fblog\u002Fgetting-started-vue-vite.md","Comenzando con Vue 3 y Vite",{"type":9,"value":24121,"toc":30543},[24122,24125,24127,24129,24133,24136,24174,24177,24187,24189,24193,24201,24204,24207,24209,24213,24216,24233,24243,24252,24255,24264,24267,24276,24279,24356,24359,24367,24387,24390,24393,24396,24404,24409,24422,24427,24439,24444,24459,24464,24478,24487,24494,24521,24524,24532,24541,24543,24547,24550,24799,24806,24814,24827,24831,24909,24913,24916,24926,25318,25328,25333,25828,25835,25842,25849,25860,25862,25866,25875,26073,26076,26137,26144,26392,26409,26415,26763,26776,26781,27032,27061,27064,27091,27099,27108,27119,27121,27124,27126,27130,27133,27136,27142,27353,27367,27712,27727,27730,27750,27756,27758,27762,27765,27772,27778,28037,28052,28058,28280,28289,28606,28612,28615,28638,28642,28652,28662,28671,28675,28681,28726,28729,28752,28756,28763,28770,28773,28804,28807,28809,28813,28820,28833,28836,28911,28921,28927,28930,28953,28955,28959,28968,28977,28980,28998,29004,29252,29259,29300,29307,29549,29556,29568,29573,30178,30184,30191,30204,30206,30210,30213,30218,30231,30240,30246,30251,30266,30288,30300,30320,30338,30357,30362,30374,30384,30389,30424,30427,30430,30439,30442,30465,30468,30484,30486,30490,30493,30533,30535,30538,30540],[12,24123,24124],{},"En esta guía, exploraremos cómo iniciar un proyecto moderno con Vue 3 y Vite, explicaremos la estructura del proyecto, como funciona una aplicación Vue, el router, Pinia, los composables, veremos algunas buenas prácticas para desarrollar aplicaciones escalables y mantenibles, y como extra publicaremos el proyecto en GitHub y veremos cómo instalar Tailwind CSS v4 para obtener estilos rápidos y responsivos.",[26,24126],{},[29,24128],{},[32,24130,24132],{"id":24131},"configurando-el-entorno","Configurando el entorno",[12,24134,24135],{},"Antes de continuar, debemos tener:",[1359,24137,24138,24151,24158,24166],{},[1362,24139,24140,24141,24144,24145,24150],{},"Node.js, cualquier versión ",[40,24142,24143],{},"LTS",". Recomiendo acostumbrarse a utilizar ",[19,24146,24149],{"target":17502,"href":24147,"rel":24148},"https:\u002F\u002Fgithub.com\u002Fcoreybutler\u002Fnvm-windows",[17504,17505],"nvm"," para manejar múltiples versiones de Node.",[1362,24152,24153,24154,24157],{},"Un gestor de paquetes (aquí usaremos ",[61,24155,24156],{},"npm",", que ya se instala con Node.js).",[1362,24159,24160,24165],{},[19,24161,24164],{"target":17502,"href":24162,"rel":24163},"https:\u002F\u002Fcode.visualstudio.com\u002F",[17504,17505],"VS Code"," actualizado",[1362,24167,24168,24173],{},[19,24169,24172],{"target":17502,"href":24170,"rel":24171},"https:\u002F\u002Fwww.desarrollolibre.net\u002Fblog\u002Fprogramacion-basica\u002Fla-guia-de-git-que-nunca-tuve",[17504,17505],"Git configurado"," correctamente",[12,24175,24176],{},"Además, instala la extensión oficial de Vue.js para VS Code:",[1359,24178,24179],{},[1362,24180,24181,24186],{},[19,24182,24185],{"target":17502,"href":24183,"rel":24184},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=Vue.volar",[17504,17505],"Vue.js (Volar)",".\nMás adelante exploraremos otros plugins útiles como ESLint, Prettier y Tailwind CSS IntelliSense.",[29,24188],{},[32,24190,24192],{"id":24191},"javascript-o-typescript","¿JavaScript o TypeScript?",[12,24194,24195,24196,133],{},"Vue 3 tiene un soporte bastante bueno para TypeScript, puedes usarlo teniendo en cuenta la ",[19,24197,24200],{"target":17502,"href":24198,"rel":24199},"https:\u002F\u002Fvuejs.org\u002Fguide\u002Ftypescript\u002Foverview.html",[17504,17505],"guía de uso oficial",[12,24202,24203],{},"No necesitas usar TypeScript en todos tus proyectos, especialmente si estás comenzando o solo quieres experimentar. Asi que mi recomendación es que valores tu contexto, la aplicación y tu equipo (si estás trabajando en uno).",[12,24205,24206],{},"En esta guía usaremos JavaScript para mantener las cosas simples.",[29,24208],{},[32,24210,24212],{"id":24211},"creando-el-proyecto-con-vite","Creando el proyecto con Vite",[12,24214,24215],{},"La forma más rápida de iniciar un proyecto Vue 3 con Vite es usando el comando (puedes ejecutarlo en cualquier carpeta donde quieras crear el proyecto, utiliza la terminal integrada de VS Code o tu terminal favorita):",[74,24217,24221],{"className":24218,"code":24219,"language":24220,"meta":79,"style":79},"language-bash shiki shiki-themes vitesse-light vitesse-dark","npm create vue@latest\n","bash",[61,24222,24223],{"__ignoreMap":79},[83,24224,24225,24227,24230],{"class":85,"line":86},[83,24226,24156],{"class":974},[83,24228,24229],{"class":250}," create",[83,24231,24232],{"class":250}," vue@latest\n",[12,24234,24235,24236,24239,24240,24242],{},"Si es primera vez que lo usas, te preguntará si deseas instalar el paquete ",[61,24237,24238],{},"create-vue",". Responde que sí (escribimos ",[61,24241,3972],{}," y damos ENTER).",[12,24244,24245,24249],{},[1882,24246],{"alt":24247,"src":24248},"Instalando create-vue","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Finstall-create-vue-package.webp",[1887,24250,24251],{},"Instalando paquete: create-vue",[12,24253,24254],{},"Nos preguntará por el nombre del proyecto, escribe el nombre que quieras:",[12,24256,24257,24261],{},[1882,24258],{"alt":24259,"src":24260},"Nombre del proyecto","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fproject-name.webp",[1887,24262,24263],{},"Asígnale un nombre a tu proyecto",[12,24265,24266],{},"Luego selecciona las opciones que necesites:",[12,24268,24269,24273],{},[1882,24270],{"alt":24271,"src":24272},"Opciones del proyecto","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fproject-options.webp",[1887,24274,24275],{},"Features disponibles al crear una app Vue",[12,24277,24278],{},"Vamos punto por punto (tal como se muestra en la imagen, nos movemos con las flechas y seleccionamos con la barra espaciadora):",[1406,24280,24281,24287,24298,24310,24316,24322,24344,24350],{},[1362,24282,24283,24286],{},[40,24284,24285],{},"TypeScript",": como mencionamos antes, usaremos JavaScript, así que ignoramos.",[1362,24288,24289,24292,24293,133],{},[40,24290,24291],{},"JSX Support",": no usaremos ",[19,24294,24297],{"target":17502,"href":24295,"rel":24296},"https:\u002F\u002Fkinsta.com\u002Fes\u002Fblog\u002Fque-es-jsx\u002F",[17504,17505],"JSX",[1362,24299,24300,24303,24304,24309],{},[40,24301,24302],{},"Router (SPA development)",": Vue Router es esencial para trabajar con Vue como SPA (Single Page Application). No ahondaremos en temas de ",[19,24305,24308],{"target":17502,"href":24306,"rel":24307},"https:\u002F\u002Fwww.geeksforgeeks.org\u002Fblogs\u002Fspa-vs-mpa-which-one-is-better-for-you\u002F",[17504,17505],"SPA vs MPA",", solo ten presente que Vue funciona como una SPA por defecto. Selecciona esta opción.",[1362,24311,24312,24315],{},[40,24313,24314],{},"Pinia (state management)",": es la librería oficial para el manejo de estado. Nos ayudará a manejar datos compartidos entre componentes. Selecciona esta opción.",[1362,24317,24318,24321],{},[40,24319,24320],{},"Vitest (unit testing)",": es el framework de testing recomendado para proyectos con Vite. No lo usaremos en esta guía.",[1362,24323,24324,24327,24328,4944,24333,21058,24338,24343],{},[40,24325,24326],{},"End-to-End Testing",": nos permitirá elegir e integrar una herramienta para pruebas E2E (",[19,24329,24332],{"target":17502,"href":24330,"rel":24331},"https:\u002F\u002Fplaywright.dev\u002F",[17504,17505],"Playwright",[19,24334,24337],{"target":17502,"href":24335,"rel":24336},"https:\u002F\u002Fwww.cypress.io\u002F",[17504,17505],"Cypress",[19,24339,24342],{"target":17502,"href":24340,"rel":24341},"https:\u002F\u002Fnightwatchjs.org\u002F",[17504,17505],"Nightwatch","). No lo usaremos en esta guía.",[1362,24345,24346,24349],{},[40,24347,24348],{},"ESLint (error prevention)",": es una herramienta para mantener la calidad del código, ayudando a detectar errores y mantener un estilo consistente. Recomiendo mucho su uso, aunque es importante personalizarlo según tu equipo y proyecto. La seleccionaremos para explorarla un poco más adelante.",[1362,24351,24352,24355],{},[40,24353,24354],{},"Prettier (code formatting)",": es una herramienta para formatear el código automáticamente. En este caso la seleccionaremos también para explorarla.",[12,24357,24358],{},"Presionamos ENTER y ahora nos preguntará sobre algunas features experimentales de Vite:",[12,24360,24361,24365],{},[1882,24362],{"alt":24363,"src":24364},"Features experimentales de Vite","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fproject-experimental-options.webp",[1887,24366,24363],{},[1406,24368,24369,24381],{},[1362,24370,24371,24374,24375,24380],{},[40,24372,24373],{},"Oxlint",": es un nuevo linter, parte de ",[19,24376,24379],{"target":17502,"href":24377,"rel":24378},"https:\u002F\u002Foxc.rs\u002F",[17504,17505],"OXC",", una nueva colección de herramientas de javascript escritas en Rust, Oxlint es en extremo rápido y promete bastante, sin embargo como se menciona en su web, aún tiene sus detalles, así que por ahora recomiendo seguir usando ESLint. Ignoramos esta opción.",[1362,24382,24383,24386],{},[40,24384,24385],{},"rolldown vite (experimental)",": Rolldown-vite es una bifurcación de Vite que utiliza Rolldown en lugar de Rollup y esbuild, con el objetivo de obtener el máximo rendimiento. Pronto se convertirá en el paquete por defecto, por ahora ignoremos esta opción.",[12,24388,24389],{},"Continuamos presionando ENTER.",[12,24391,24392],{},"Nos preguntará si queremos empezar con un proyecto totalmente en blanco o con ejemplos. Si es tu primera vez, te recomiendo seleccionar \"No\" para que puedas ver una estructura básica con ejemplos. Esa será la opción que seleccionaremos aquí.",[12,24394,24395],{},"Vite creará la estructura inicial del proyecto y nos dará algunos comandos útiles, vamos ejecutando uno por uno:",[12,24397,24398,24402],{},[1882,24399],{"alt":24400,"src":24401},"Proyecto creado","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fproject-created.webp",[1887,24403,24400],{},[1406,24405,24406],{},[1362,24407,24408],{},"Primero navegamos a la carpeta del proyecto:",[74,24410,24412],{"className":24218,"code":24411,"language":24220,"meta":79,"style":79},"cd nombre-del-proyecto\n",[61,24413,24414],{"__ignoreMap":79},[83,24415,24416,24419],{"class":85,"line":86},[83,24417,24418],{"class":307},"cd",[83,24420,24421],{"class":250}," nombre-del-proyecto\n",[1406,24423,24424],{"start":103},[1362,24425,24426],{},"Instalamos las dependencias (esto puede tardar unos minutos dependiendo de tu conexión):",[74,24428,24430],{"className":24218,"code":24429,"language":24220,"meta":79,"style":79},"npm install\n",[61,24431,24432],{"__ignoreMap":79},[83,24433,24434,24436],{"class":85,"line":86},[83,24435,24156],{"class":974},[83,24437,24438],{"class":250}," install\n",[1406,24440,24441],{"start":116},[1362,24442,24443],{},"Este comando es para correr Prettier, no tendrá ningún efecto porque no hemos modificado nada aún, pero es bueno tenerlo presente:",[74,24445,24447],{"className":24218,"code":24446,"language":24220,"meta":79,"style":79},"npm run format\n",[61,24448,24449],{"__ignoreMap":79},[83,24450,24451,24453,24456],{"class":85,"line":86},[83,24452,24156],{"class":974},[83,24454,24455],{"class":250}," run",[83,24457,24458],{"class":250}," format\n",[1406,24460,24461],{"start":124},[1362,24462,24463],{},"Finalmente, iniciamos el servidor de desarrollo:",[74,24465,24467],{"className":24218,"code":24466,"language":24220,"meta":79,"style":79},"npm run dev\n",[61,24468,24469],{"__ignoreMap":79},[83,24470,24471,24473,24475],{"class":85,"line":86},[83,24472,24156],{"class":974},[83,24474,24455],{"class":250},[83,24476,24477],{"class":250}," dev\n",[12,24479,24480,24484],{},[1882,24481],{"alt":24482,"src":24483},"Servidor de desarrollo corriendo","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fdev-server-running.webp",[1887,24485,24486],{},"Servidor de desarrollo levantado",[12,24488,24489,24490,24493],{},"Vite corre el servidor de desarrollo en ",[61,24491,24492],{},"http:\u002F\u002Flocalhost:5173\u002F"," (el puerto puede variar si el 5173 ya está en uso (5174, 5175, etc.) ).",[2073,24495,24496,24499,24513],{},[12,24497,24498],{},"El puerto 5173 es un guiño al propio Vite:",[1359,24500,24501,24504,24507,24510],{},[1362,24502,24503],{},"5 = V",[1362,24505,24506],{},"1 = I",[1362,24508,24509],{},"7 = T",[1362,24511,24512],{},"3 = E",[12,24514,24515,24516,133],{},"Aunque más allá de eso, Vite utiliza el puerto 5173 porque es poco habitual en entornos de desarrollo, lo que reduce la probabilidad de conflictos con otros servidores locales. Vía ",[19,24517,24520],{"target":17502,"href":24518,"rel":24519},"https:\u002F\u002Fmedium.com\u002F@bishakhghosh0\u002Fwhy-localhost-5173-is-every-frontend-developers-best-friend-b3bb5b6fb1db",[17504,17505],"Why localhost:5173 is Every Frontend Developer’s Best Friend",[12,24522,24523],{},"Si entramos a esa URL en nuestro navegador, veremos la app Vue corriendo:",[12,24525,24526,24530],{},[1882,24527],{"alt":24528,"src":24529},"App Vue corriendo","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fvue-app-running.webp",[1887,24531,24528],{},[12,24533,24534,24535,24540],{},"El equipo de Vue comparte varios recursos oficiales para aprender más sobre el framework, comenzando por la ",[19,24536,24539],{"target":17502,"href":24537,"rel":24538},"https:\u002F\u002Fvuejs.org\u002Fguide\u002Fintroduction.html",[17504,17505],"documentación oficial",". Explora cada enlace para aprender y conocer sobre todo el ecosistema.",[29,24542],{},[32,24544,24546],{"id":24545},"estructura-del-proyecto","Estructura del proyecto",[12,24548,24549],{},"Pasemos a ver la estructura inicial, abre el proyecto en tu editor de código favorito (recomiendo VS Code):",[74,24551,24553],{"className":24218,"code":24552,"language":24220,"meta":79,"style":79},"my-vue-app\u002F\n├── .vscode\u002F              # (Si estás en VS Code) Configuración de Visual Studio Code\n├── node_modules\u002F         # Dependencias del proyecto, generadas al instalar los paquetes\n├── public\u002F               # Archivos estáticos\n├── src\u002F                  # Código fuente de la aplicación\n│   ├── assets\u002F           # Recursos como imágenes y estilos\n│   ├── components\u002F       # Componentes Vue reutilizables\n│   ├── router\u002F           # Configuración de Vue Router\n│   ├── store\u002F            # Configuración de Pinia\n│   ├── views\u002F            # Vistas para las rutas\n│   ├── App.vue           # Componente raíz de la aplicación\n│   └── main.js           # Punto de entrada de la aplicación\n├── .editorconfig         # Configuración de EditorConfig\n├── .gitattributes        # Configuración de Git\n├── .gitignore            # Archivos y carpetas ignoradas por Git\n├── .prettierrc.json      # Configuración de Prettier\n├── eslint.config.js      # Configuración de ESLint\n├── index.html            # Archivo HTML principal\n├── jsconfig.json         # Configuración de JavaScript para el editor\n├── package-lock.json     # Versiones exactas de las dependencias (autogenerado)\n├── package.json          # Información del proyecto y scripts\n├── README.md             # Documentación del proyecto\n└── vite.config.js        # Configuración de Vite\n",[61,24554,24555,24560,24571,24581,24591,24601,24615,24627,24639,24651,24663,24675,24688,24698,24708,24718,24728,24738,24748,24758,24768,24778,24788],{"__ignoreMap":79},[83,24556,24557],{"class":85,"line":86},[83,24558,24559],{"class":974},"my-vue-app\u002F\n",[83,24561,24562,24565,24568],{"class":85,"line":103},[83,24563,24564],{"class":974},"├──",[83,24566,24567],{"class":250}," .vscode\u002F",[83,24569,24570],{"class":167},"              # (Si estás en VS Code) Configuración de Visual Studio Code\n",[83,24572,24573,24575,24578],{"class":85,"line":116},[83,24574,24564],{"class":974},[83,24576,24577],{"class":250}," node_modules\u002F",[83,24579,24580],{"class":167},"         # Dependencias del proyecto, generadas al instalar los paquetes\n",[83,24582,24583,24585,24588],{"class":85,"line":124},[83,24584,24564],{"class":974},[83,24586,24587],{"class":250}," public\u002F",[83,24589,24590],{"class":167},"               # Archivos estáticos\n",[83,24592,24593,24595,24598],{"class":85,"line":144},[83,24594,24564],{"class":974},[83,24596,24597],{"class":250}," src\u002F",[83,24599,24600],{"class":167},"                  # Código fuente de la aplicación\n",[83,24602,24603,24606,24609,24612],{"class":85,"line":157},[83,24604,24605],{"class":974},"│",[83,24607,24608],{"class":250},"   ├──",[83,24610,24611],{"class":250}," assets\u002F",[83,24613,24614],{"class":167},"           # Recursos como imágenes y estilos\n",[83,24616,24617,24619,24621,24624],{"class":85,"line":164},[83,24618,24605],{"class":974},[83,24620,24608],{"class":250},[83,24622,24623],{"class":250}," components\u002F",[83,24625,24626],{"class":167},"       # Componentes Vue reutilizables\n",[83,24628,24629,24631,24633,24636],{"class":85,"line":171},[83,24630,24605],{"class":974},[83,24632,24608],{"class":250},[83,24634,24635],{"class":250}," router\u002F",[83,24637,24638],{"class":167},"           # Configuración de Vue Router\n",[83,24640,24641,24643,24645,24648],{"class":85,"line":197},[83,24642,24605],{"class":974},[83,24644,24608],{"class":250},[83,24646,24647],{"class":250}," store\u002F",[83,24649,24650],{"class":167},"            # Configuración de Pinia\n",[83,24652,24653,24655,24657,24660],{"class":85,"line":212},[83,24654,24605],{"class":974},[83,24656,24608],{"class":250},[83,24658,24659],{"class":250}," views\u002F",[83,24661,24662],{"class":167},"            # Vistas para las rutas\n",[83,24664,24665,24667,24669,24672],{"class":85,"line":217},[83,24666,24605],{"class":974},[83,24668,24608],{"class":250},[83,24670,24671],{"class":250}," App.vue",[83,24673,24674],{"class":167},"           # Componente raíz de la aplicación\n",[83,24676,24677,24679,24682,24685],{"class":85,"line":223},[83,24678,24605],{"class":974},[83,24680,24681],{"class":250},"   └──",[83,24683,24684],{"class":250}," main.js",[83,24686,24687],{"class":167},"           # Punto de entrada de la aplicación\n",[83,24689,24690,24692,24695],{"class":85,"line":235},[83,24691,24564],{"class":974},[83,24693,24694],{"class":250}," .editorconfig",[83,24696,24697],{"class":167},"         # Configuración de EditorConfig\n",[83,24699,24700,24702,24705],{"class":85,"line":279},[83,24701,24564],{"class":974},[83,24703,24704],{"class":250}," .gitattributes",[83,24706,24707],{"class":167},"        # Configuración de Git\n",[83,24709,24710,24712,24715],{"class":85,"line":290},[83,24711,24564],{"class":974},[83,24713,24714],{"class":250}," .gitignore",[83,24716,24717],{"class":167},"            # Archivos y carpetas ignoradas por Git\n",[83,24719,24720,24722,24725],{"class":85,"line":295},[83,24721,24564],{"class":974},[83,24723,24724],{"class":250}," .prettierrc.json",[83,24726,24727],{"class":167},"      # Configuración de Prettier\n",[83,24729,24730,24732,24735],{"class":85,"line":319},[83,24731,24564],{"class":974},[83,24733,24734],{"class":250}," eslint.config.js",[83,24736,24737],{"class":167},"      # Configuración de ESLint\n",[83,24739,24740,24742,24745],{"class":85,"line":357},[83,24741,24564],{"class":974},[83,24743,24744],{"class":250}," index.html",[83,24746,24747],{"class":167},"            # Archivo HTML principal\n",[83,24749,24750,24752,24755],{"class":85,"line":392},[83,24751,24564],{"class":974},[83,24753,24754],{"class":250}," jsconfig.json",[83,24756,24757],{"class":167},"         # Configuración de JavaScript para el editor\n",[83,24759,24760,24762,24765],{"class":85,"line":421},[83,24761,24564],{"class":974},[83,24763,24764],{"class":250}," package-lock.json",[83,24766,24767],{"class":167},"     # Versiones exactas de las dependencias (autogenerado)\n",[83,24769,24770,24772,24775],{"class":85,"line":456},[83,24771,24564],{"class":974},[83,24773,24774],{"class":250}," package.json",[83,24776,24777],{"class":167},"          # Información del proyecto y scripts\n",[83,24779,24780,24782,24785],{"class":85,"line":477},[83,24781,24564],{"class":974},[83,24783,24784],{"class":250}," README.md",[83,24786,24787],{"class":167},"             # Documentación del proyecto\n",[83,24789,24790,24793,24796],{"class":85,"line":483},[83,24791,24792],{"class":974},"└──",[83,24794,24795],{"class":250}," vite.config.js",[83,24797,24798],{"class":167},"        # Configuración de Vite\n",[12,24800,24801,24802,24805],{},"La estructura puede variar ligeramente dependiendo de las opciones seleccionadas al crear el proyecto (por ejemplo, si se incluye o no ESLint o Pinia). Además, si estás usando VS Code es probable que veas la carpeta ",[61,24803,24804],{},".vscode\u002F"," con configuraciones específicas para el editor y que algunos archivos los veas \"agrupados\":",[12,24807,24808,24812],{},[1882,24809],{"alt":24810,"src":24811},"Estructura del proyecto en VS Code","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fproject-structure-nested.webp",[1887,24813,24810],{},[12,24815,24816,24817,24820,24821,24823,24824,133],{},"Esto es solo una forma visual que tiene VS Code para organizar los archivos, puedes mostrarlos individualmente (opción que prefiero) cambiando el valor de ",[61,24818,24819],{},"\"explorer.fileNesting.enabled\""," a ",[61,24822,6169],{}," en el archivo ",[61,24825,24826],{},".vscode\\settings.json",[53,24828,24830],{"id":24829},"entendiendo-las-carpetas-principales","Entendiendo las carpetas principales",[1359,24832,24833,24839],{},[1362,24834,24835,24838],{},[61,24836,24837],{},"public\u002F",": Aquí van los archivos estáticos que no serán procesados por Vite. Puedes colocar imágenes, fuentes u otros recursos que necesites servir directamente.",[1362,24840,24841,24844,24845],{},[61,24842,24843],{},"src\u002F",": Esta es la carpeta más importante, contiene todo el código fuente de tu aplicación. Aquí tenemos:\n",[1359,24846,24847,24853,24859,24871,24887,24897,24903],{},[1362,24848,24849,24852],{},[61,24850,24851],{},"assets\u002F",": Aquí van los recursos como imágenes, fuentes y estilos CSS.",[1362,24854,24855,24858],{},[61,24856,24857],{},"components\u002F",": Aquí van los componentes Vue globales, reutilizables, que puedes usar en diferentes partes de tu aplicación, por ejemplo, botones, tarjetas, modales, etc.",[1362,24860,24861,24864,24865,24870],{},[61,24862,24863],{},"router\u002F",": Aquí va la configuración de ",[19,24866,24869],{"href":24867,"target":17502,"rel":24868},"https:\u002F\u002Frouter.vuejs.org\u002F",[17504,17505],"Vue Router",", donde defines las rutas de tu aplicación y cómo se navega entre ellas, así como la posible configuración de guards, lazy loading, etc.",[1362,24872,24873,24864,24876,24881,24882],{},[61,24874,24875],{},"store\u002F",[19,24877,24880],{"href":24878,"target":17502,"rel":24879},"https:\u002F\u002Fpinia.vuejs.org\u002F",[17504,17505],"Pinia",", donde defines el ",[19,24883,24886],{"href":24884,"target":17502,"rel":24885},"https:\u002F\u002Fkinsta.com\u002Fes\u002Fblog\u002Fvue-pinia\u002F",[17504,17505],"estado global de tu aplicación. ",[1362,24888,24889,24892,24893,24896],{},[61,24890,24891],{},"views\u002F",": Aquí van las vistas principales que corresponden a las rutas definidas en Vue Router. Cada vista generalmente representa una página completa, caso contrario a los componentes que son partes más pequeñas y reutilizables. A final todos son archivos ",[61,24894,24895],{},".vue",", por lo que la diferencia radica en su propósito y uso.",[1362,24898,24899,24902],{},[61,24900,24901],{},"App.vue",": Este es el componente raíz de tu aplicación, donde se monta todo (ya explicaremos más adelante).",[1362,24904,24905,24908],{},[61,24906,24907],{},"main.js",": Este es el punto de entrada de tu aplicación, donde se inicializa Vue, se configuran los plugins (como Vue Router y Pinia) y se monta la aplicación en el DOM.",[53,24910,24912],{"id":24911},"es-suficiente-esta-estructura","¿Es suficiente esta estructura?",[12,24914,24915],{},"Es una estructura básica que por ahora está bien. A medida que tu aplicación crezca normalmente se busca organizar mejor el código. Aquí hay dos propuestas:",[1359,24917,24918],{},[1362,24919,24920,24921,1966,24923,24925],{},"Crear subcarpetas por módulo\u002Ffuncionalidad dentro de las distintas carpetas, como ",[61,24922,24857],{},[61,24924,24891],{},". Por ejemplo:",[74,24927,24929],{"className":24218,"code":24928,"language":24220,"meta":79,"style":79},"my-vue-app\u002F\n├── src\u002F\n│   ├── assets\u002F\n│   ├── components\u002F\n│   │   ├── auth\u002F\n│   │   │   ├── LoginForm.vue\n│   │   │   └── RegisterForm.vue\n│   │   ├── dashboard\u002F\n│   │   │   ├── StatsCard.vue\n│   │   │   └── ChartWidget.vue\n│   │   └── shared\u002F\n│   │       ├── BaseButton.vue\n│   │       └── BaseModal.vue\n│   │\n│   ├── views\u002F\n│   │   ├── auth\u002F\n│   │   │   ├── LoginView.vue\n│   │   │   └── RegisterView.vue\n│   │   ├── dashboard\u002F\n│   │   │   └── DashboardView.vue\n│   │   └── home\u002F\n│   │       └── HomeView.vue\n│   │\n│   ├── store\u002F\n│   │   ├── auth\u002F\n│   │   │   └── auth.store.js\n│   │   ├── dashboard\u002F\n│   │   │   └── dashboard.store.js\n│   │   └── shared\u002F\n│   │       └── ui.store.js\n│   │\n│   ├── router\u002F\n│   │   ├── auth.routes.js\n│   │   ├── dashboard.routes.js\n│   │   └── index.js\n│   │\n│   ├── ...\n├── ...\n",[61,24930,24931,24935,24942,24951,24960,24972,24985,24998,25009,25022,25035,25046,25058,25070,25077,25086,25096,25109,25122,25132,25145,25156,25167,25173,25182,25192,25205,25215,25228,25238,25249,25255,25264,25275,25286,25297,25303,25312],{"__ignoreMap":79},[83,24932,24933],{"class":85,"line":86},[83,24934,24559],{"class":974},[83,24936,24937,24939],{"class":85,"line":103},[83,24938,24564],{"class":974},[83,24940,24941],{"class":250}," src\u002F\n",[83,24943,24944,24946,24948],{"class":85,"line":116},[83,24945,24605],{"class":974},[83,24947,24608],{"class":250},[83,24949,24950],{"class":250}," assets\u002F\n",[83,24952,24953,24955,24957],{"class":85,"line":124},[83,24954,24605],{"class":974},[83,24956,24608],{"class":250},[83,24958,24959],{"class":250}," components\u002F\n",[83,24961,24962,24964,24967,24969],{"class":85,"line":144},[83,24963,24605],{"class":974},[83,24965,24966],{"class":250},"   │",[83,24968,24608],{"class":250},[83,24970,24971],{"class":250}," auth\u002F\n",[83,24973,24974,24976,24978,24980,24982],{"class":85,"line":157},[83,24975,24605],{"class":974},[83,24977,24966],{"class":250},[83,24979,24966],{"class":250},[83,24981,24608],{"class":250},[83,24983,24984],{"class":250}," LoginForm.vue\n",[83,24986,24987,24989,24991,24993,24995],{"class":85,"line":164},[83,24988,24605],{"class":974},[83,24990,24966],{"class":250},[83,24992,24966],{"class":250},[83,24994,24681],{"class":250},[83,24996,24997],{"class":250}," RegisterForm.vue\n",[83,24999,25000,25002,25004,25006],{"class":85,"line":171},[83,25001,24605],{"class":974},[83,25003,24966],{"class":250},[83,25005,24608],{"class":250},[83,25007,25008],{"class":250}," dashboard\u002F\n",[83,25010,25011,25013,25015,25017,25019],{"class":85,"line":197},[83,25012,24605],{"class":974},[83,25014,24966],{"class":250},[83,25016,24966],{"class":250},[83,25018,24608],{"class":250},[83,25020,25021],{"class":250}," StatsCard.vue\n",[83,25023,25024,25026,25028,25030,25032],{"class":85,"line":212},[83,25025,24605],{"class":974},[83,25027,24966],{"class":250},[83,25029,24966],{"class":250},[83,25031,24681],{"class":250},[83,25033,25034],{"class":250}," ChartWidget.vue\n",[83,25036,25037,25039,25041,25043],{"class":85,"line":217},[83,25038,24605],{"class":974},[83,25040,24966],{"class":250},[83,25042,24681],{"class":250},[83,25044,25045],{"class":250}," shared\u002F\n",[83,25047,25048,25050,25052,25055],{"class":85,"line":223},[83,25049,24605],{"class":974},[83,25051,24966],{"class":250},[83,25053,25054],{"class":250},"       ├──",[83,25056,25057],{"class":250}," BaseButton.vue\n",[83,25059,25060,25062,25064,25067],{"class":85,"line":235},[83,25061,24605],{"class":974},[83,25063,24966],{"class":250},[83,25065,25066],{"class":250},"       └──",[83,25068,25069],{"class":250}," BaseModal.vue\n",[83,25071,25072,25074],{"class":85,"line":279},[83,25073,24605],{"class":974},[83,25075,25076],{"class":250},"   │\n",[83,25078,25079,25081,25083],{"class":85,"line":290},[83,25080,24605],{"class":974},[83,25082,24608],{"class":250},[83,25084,25085],{"class":250}," views\u002F\n",[83,25087,25088,25090,25092,25094],{"class":85,"line":295},[83,25089,24605],{"class":974},[83,25091,24966],{"class":250},[83,25093,24608],{"class":250},[83,25095,24971],{"class":250},[83,25097,25098,25100,25102,25104,25106],{"class":85,"line":319},[83,25099,24605],{"class":974},[83,25101,24966],{"class":250},[83,25103,24966],{"class":250},[83,25105,24608],{"class":250},[83,25107,25108],{"class":250}," LoginView.vue\n",[83,25110,25111,25113,25115,25117,25119],{"class":85,"line":357},[83,25112,24605],{"class":974},[83,25114,24966],{"class":250},[83,25116,24966],{"class":250},[83,25118,24681],{"class":250},[83,25120,25121],{"class":250}," RegisterView.vue\n",[83,25123,25124,25126,25128,25130],{"class":85,"line":392},[83,25125,24605],{"class":974},[83,25127,24966],{"class":250},[83,25129,24608],{"class":250},[83,25131,25008],{"class":250},[83,25133,25134,25136,25138,25140,25142],{"class":85,"line":421},[83,25135,24605],{"class":974},[83,25137,24966],{"class":250},[83,25139,24966],{"class":250},[83,25141,24681],{"class":250},[83,25143,25144],{"class":250}," DashboardView.vue\n",[83,25146,25147,25149,25151,25153],{"class":85,"line":456},[83,25148,24605],{"class":974},[83,25150,24966],{"class":250},[83,25152,24681],{"class":250},[83,25154,25155],{"class":250}," home\u002F\n",[83,25157,25158,25160,25162,25164],{"class":85,"line":477},[83,25159,24605],{"class":974},[83,25161,24966],{"class":250},[83,25163,25066],{"class":250},[83,25165,25166],{"class":250}," HomeView.vue\n",[83,25168,25169,25171],{"class":85,"line":483},[83,25170,24605],{"class":974},[83,25172,25076],{"class":250},[83,25174,25175,25177,25179],{"class":85,"line":489},[83,25176,24605],{"class":974},[83,25178,24608],{"class":250},[83,25180,25181],{"class":250}," store\u002F\n",[83,25183,25184,25186,25188,25190],{"class":85,"line":495},[83,25185,24605],{"class":974},[83,25187,24966],{"class":250},[83,25189,24608],{"class":250},[83,25191,24971],{"class":250},[83,25193,25194,25196,25198,25200,25202],{"class":85,"line":506},[83,25195,24605],{"class":974},[83,25197,24966],{"class":250},[83,25199,24966],{"class":250},[83,25201,24681],{"class":250},[83,25203,25204],{"class":250}," auth.store.js\n",[83,25206,25207,25209,25211,25213],{"class":85,"line":519},[83,25208,24605],{"class":974},[83,25210,24966],{"class":250},[83,25212,24608],{"class":250},[83,25214,25008],{"class":250},[83,25216,25217,25219,25221,25223,25225],{"class":85,"line":542},[83,25218,24605],{"class":974},[83,25220,24966],{"class":250},[83,25222,24966],{"class":250},[83,25224,24681],{"class":250},[83,25226,25227],{"class":250}," dashboard.store.js\n",[83,25229,25230,25232,25234,25236],{"class":85,"line":561},[83,25231,24605],{"class":974},[83,25233,24966],{"class":250},[83,25235,24681],{"class":250},[83,25237,25045],{"class":250},[83,25239,25240,25242,25244,25246],{"class":85,"line":580},[83,25241,24605],{"class":974},[83,25243,24966],{"class":250},[83,25245,25066],{"class":250},[83,25247,25248],{"class":250}," ui.store.js\n",[83,25250,25251,25253],{"class":85,"line":595},[83,25252,24605],{"class":974},[83,25254,25076],{"class":250},[83,25256,25257,25259,25261],{"class":85,"line":601},[83,25258,24605],{"class":974},[83,25260,24608],{"class":250},[83,25262,25263],{"class":250}," router\u002F\n",[83,25265,25266,25268,25270,25272],{"class":85,"line":606},[83,25267,24605],{"class":974},[83,25269,24966],{"class":250},[83,25271,24608],{"class":250},[83,25273,25274],{"class":250}," auth.routes.js\n",[83,25276,25277,25279,25281,25283],{"class":85,"line":636},[83,25278,24605],{"class":974},[83,25280,24966],{"class":250},[83,25282,24608],{"class":250},[83,25284,25285],{"class":250}," dashboard.routes.js\n",[83,25287,25288,25290,25292,25294],{"class":85,"line":662},[83,25289,24605],{"class":974},[83,25291,24966],{"class":250},[83,25293,24681],{"class":250},[83,25295,25296],{"class":250}," index.js\n",[83,25298,25299,25301],{"class":85,"line":667},[83,25300,24605],{"class":974},[83,25302,25076],{"class":250},[83,25304,25305,25307,25309],{"class":85,"line":673},[83,25306,24605],{"class":974},[83,25308,24608],{"class":250},[83,25310,25311],{"class":250}," ...\n",[83,25313,25314,25316],{"class":85,"line":703},[83,25315,24564],{"class":974},[83,25317,25311],{"class":250},[12,25319,25320,25323,25324,25327],{},[40,25321,25322],{},"Puedes usar un enfoque similar a este"," en apps pequeñas o medianas, con poca gente trabajando, en las que quieres un poco más de orden sin complicarte demasiado y sin cambiar demasiado la estructura original que propone Vue. ",[40,25325,25326],{},"La limitante"," es que a medida que la app crece, puede volverse difícil manejar dependencias entre módulos y mantener el código organizado, porque todo está disperso en varias carpetas.",[1359,25329,25330],{},[1362,25331,25332],{},"En otros casos, puedes optar por una estructura basada en funcionalidades o módulos, donde cada uno tiene su propia carpeta que contiene componentes, vistas, y lógica relacionada. Por ejemplo:",[74,25334,25336],{"className":24218,"code":25335,"language":24220,"meta":79,"style":79},"my-vue-app\u002F\n├── src\u002F\n│   ├── modules\u002F\n│   │   ├── auth\u002F                     # Si el módulo es pequeño, puedes omitir la división en carpetas\n│   │   │   ├── components\u002F\n│   │   │   │   └── LoginForm.vue\n│   │   │   ├── views\u002F\n│   │   │   │   └── LoginView.vue\n│   │   │   ├── store\u002F\n│   │   │   │   └── auth.store.js\n│   │   │   ├── router\u002F\n│   │   │   │   └── auth.routes.js\n│   │   │   └── index.js\n│   │   │\n│   │   ├── dashboard\u002F\n│   │   │   ├── components\u002F\n│   │   │   ├── views\u002F\n│   │   │   ├── store\u002F\n│   │   │   ├── router\u002F\n│   │   │   └── index.js\n│   │   │\n│   │   └── users\u002F\n│   │       ├── components\u002F\n│   │       ├── views\u002F\n│   │       ├── store\u002F\n│   │       ├── router\u002F\n│   │       └── index.js\n│   │\n│   ├── shared\u002F\n│   │   ├── components\u002F\n│   │   │   ├── BaseButton.vue\n│   │   │   └── BaseModal.vue\n│   │   ├── composables\u002F\n│   │   │   └── useFetch.js\n│   │   ├── store\u002F\n│   │   │   └── ui.store.js\n│   │   ├── utils\u002F\n│   │   │   └── formatDate.js\n│   │   └── constants\u002F\n│   │       └── roles.js\n│   │\n│   ├── router\u002F\n│   │   └── index.js                # Archivo principal del router que importa las rutas de los módulos\n│   │                               # (los guards van aquí)\n│   ├── ...\n├── ...\n",[61,25337,25338,25342,25348,25357,25371,25383,25397,25409,25423,25435,25449,25461,25475,25487,25495,25505,25517,25529,25541,25553,25565,25573,25584,25594,25604,25614,25624,25634,25640,25648,25658,25670,25682,25693,25706,25716,25728,25739,25752,25763,25774,25780,25788,25802,25812,25821],{"__ignoreMap":79},[83,25339,25340],{"class":85,"line":86},[83,25341,24559],{"class":974},[83,25343,25344,25346],{"class":85,"line":103},[83,25345,24564],{"class":974},[83,25347,24941],{"class":250},[83,25349,25350,25352,25354],{"class":85,"line":116},[83,25351,24605],{"class":974},[83,25353,24608],{"class":250},[83,25355,25356],{"class":250}," modules\u002F\n",[83,25358,25359,25361,25363,25365,25368],{"class":85,"line":124},[83,25360,24605],{"class":974},[83,25362,24966],{"class":250},[83,25364,24608],{"class":250},[83,25366,25367],{"class":250}," auth\u002F",[83,25369,25370],{"class":167},"                     # Si el módulo es pequeño, puedes omitir la división en carpetas\n",[83,25372,25373,25375,25377,25379,25381],{"class":85,"line":144},[83,25374,24605],{"class":974},[83,25376,24966],{"class":250},[83,25378,24966],{"class":250},[83,25380,24608],{"class":250},[83,25382,24959],{"class":250},[83,25384,25385,25387,25389,25391,25393,25395],{"class":85,"line":157},[83,25386,24605],{"class":974},[83,25388,24966],{"class":250},[83,25390,24966],{"class":250},[83,25392,24966],{"class":250},[83,25394,24681],{"class":250},[83,25396,24984],{"class":250},[83,25398,25399,25401,25403,25405,25407],{"class":85,"line":164},[83,25400,24605],{"class":974},[83,25402,24966],{"class":250},[83,25404,24966],{"class":250},[83,25406,24608],{"class":250},[83,25408,25085],{"class":250},[83,25410,25411,25413,25415,25417,25419,25421],{"class":85,"line":171},[83,25412,24605],{"class":974},[83,25414,24966],{"class":250},[83,25416,24966],{"class":250},[83,25418,24966],{"class":250},[83,25420,24681],{"class":250},[83,25422,25108],{"class":250},[83,25424,25425,25427,25429,25431,25433],{"class":85,"line":197},[83,25426,24605],{"class":974},[83,25428,24966],{"class":250},[83,25430,24966],{"class":250},[83,25432,24608],{"class":250},[83,25434,25181],{"class":250},[83,25436,25437,25439,25441,25443,25445,25447],{"class":85,"line":212},[83,25438,24605],{"class":974},[83,25440,24966],{"class":250},[83,25442,24966],{"class":250},[83,25444,24966],{"class":250},[83,25446,24681],{"class":250},[83,25448,25204],{"class":250},[83,25450,25451,25453,25455,25457,25459],{"class":85,"line":217},[83,25452,24605],{"class":974},[83,25454,24966],{"class":250},[83,25456,24966],{"class":250},[83,25458,24608],{"class":250},[83,25460,25263],{"class":250},[83,25462,25463,25465,25467,25469,25471,25473],{"class":85,"line":223},[83,25464,24605],{"class":974},[83,25466,24966],{"class":250},[83,25468,24966],{"class":250},[83,25470,24966],{"class":250},[83,25472,24681],{"class":250},[83,25474,25274],{"class":250},[83,25476,25477,25479,25481,25483,25485],{"class":85,"line":235},[83,25478,24605],{"class":974},[83,25480,24966],{"class":250},[83,25482,24966],{"class":250},[83,25484,24681],{"class":250},[83,25486,25296],{"class":250},[83,25488,25489,25491,25493],{"class":85,"line":279},[83,25490,24605],{"class":974},[83,25492,24966],{"class":250},[83,25494,25076],{"class":250},[83,25496,25497,25499,25501,25503],{"class":85,"line":290},[83,25498,24605],{"class":974},[83,25500,24966],{"class":250},[83,25502,24608],{"class":250},[83,25504,25008],{"class":250},[83,25506,25507,25509,25511,25513,25515],{"class":85,"line":295},[83,25508,24605],{"class":974},[83,25510,24966],{"class":250},[83,25512,24966],{"class":250},[83,25514,24608],{"class":250},[83,25516,24959],{"class":250},[83,25518,25519,25521,25523,25525,25527],{"class":85,"line":319},[83,25520,24605],{"class":974},[83,25522,24966],{"class":250},[83,25524,24966],{"class":250},[83,25526,24608],{"class":250},[83,25528,25085],{"class":250},[83,25530,25531,25533,25535,25537,25539],{"class":85,"line":357},[83,25532,24605],{"class":974},[83,25534,24966],{"class":250},[83,25536,24966],{"class":250},[83,25538,24608],{"class":250},[83,25540,25181],{"class":250},[83,25542,25543,25545,25547,25549,25551],{"class":85,"line":392},[83,25544,24605],{"class":974},[83,25546,24966],{"class":250},[83,25548,24966],{"class":250},[83,25550,24608],{"class":250},[83,25552,25263],{"class":250},[83,25554,25555,25557,25559,25561,25563],{"class":85,"line":421},[83,25556,24605],{"class":974},[83,25558,24966],{"class":250},[83,25560,24966],{"class":250},[83,25562,24681],{"class":250},[83,25564,25296],{"class":250},[83,25566,25567,25569,25571],{"class":85,"line":456},[83,25568,24605],{"class":974},[83,25570,24966],{"class":250},[83,25572,25076],{"class":250},[83,25574,25575,25577,25579,25581],{"class":85,"line":477},[83,25576,24605],{"class":974},[83,25578,24966],{"class":250},[83,25580,24681],{"class":250},[83,25582,25583],{"class":250}," users\u002F\n",[83,25585,25586,25588,25590,25592],{"class":85,"line":483},[83,25587,24605],{"class":974},[83,25589,24966],{"class":250},[83,25591,25054],{"class":250},[83,25593,24959],{"class":250},[83,25595,25596,25598,25600,25602],{"class":85,"line":489},[83,25597,24605],{"class":974},[83,25599,24966],{"class":250},[83,25601,25054],{"class":250},[83,25603,25085],{"class":250},[83,25605,25606,25608,25610,25612],{"class":85,"line":495},[83,25607,24605],{"class":974},[83,25609,24966],{"class":250},[83,25611,25054],{"class":250},[83,25613,25181],{"class":250},[83,25615,25616,25618,25620,25622],{"class":85,"line":506},[83,25617,24605],{"class":974},[83,25619,24966],{"class":250},[83,25621,25054],{"class":250},[83,25623,25263],{"class":250},[83,25625,25626,25628,25630,25632],{"class":85,"line":519},[83,25627,24605],{"class":974},[83,25629,24966],{"class":250},[83,25631,25066],{"class":250},[83,25633,25296],{"class":250},[83,25635,25636,25638],{"class":85,"line":542},[83,25637,24605],{"class":974},[83,25639,25076],{"class":250},[83,25641,25642,25644,25646],{"class":85,"line":561},[83,25643,24605],{"class":974},[83,25645,24608],{"class":250},[83,25647,25045],{"class":250},[83,25649,25650,25652,25654,25656],{"class":85,"line":580},[83,25651,24605],{"class":974},[83,25653,24966],{"class":250},[83,25655,24608],{"class":250},[83,25657,24959],{"class":250},[83,25659,25660,25662,25664,25666,25668],{"class":85,"line":595},[83,25661,24605],{"class":974},[83,25663,24966],{"class":250},[83,25665,24966],{"class":250},[83,25667,24608],{"class":250},[83,25669,25057],{"class":250},[83,25671,25672,25674,25676,25678,25680],{"class":85,"line":601},[83,25673,24605],{"class":974},[83,25675,24966],{"class":250},[83,25677,24966],{"class":250},[83,25679,24681],{"class":250},[83,25681,25069],{"class":250},[83,25683,25684,25686,25688,25690],{"class":85,"line":606},[83,25685,24605],{"class":974},[83,25687,24966],{"class":250},[83,25689,24608],{"class":250},[83,25691,25692],{"class":250}," composables\u002F\n",[83,25694,25695,25697,25699,25701,25703],{"class":85,"line":636},[83,25696,24605],{"class":974},[83,25698,24966],{"class":250},[83,25700,24966],{"class":250},[83,25702,24681],{"class":250},[83,25704,25705],{"class":250}," useFetch.js\n",[83,25707,25708,25710,25712,25714],{"class":85,"line":662},[83,25709,24605],{"class":974},[83,25711,24966],{"class":250},[83,25713,24608],{"class":250},[83,25715,25181],{"class":250},[83,25717,25718,25720,25722,25724,25726],{"class":85,"line":667},[83,25719,24605],{"class":974},[83,25721,24966],{"class":250},[83,25723,24966],{"class":250},[83,25725,24681],{"class":250},[83,25727,25248],{"class":250},[83,25729,25730,25732,25734,25736],{"class":85,"line":673},[83,25731,24605],{"class":974},[83,25733,24966],{"class":250},[83,25735,24608],{"class":250},[83,25737,25738],{"class":250}," utils\u002F\n",[83,25740,25741,25743,25745,25747,25749],{"class":85,"line":703},[83,25742,24605],{"class":974},[83,25744,24966],{"class":250},[83,25746,24966],{"class":250},[83,25748,24681],{"class":250},[83,25750,25751],{"class":250}," formatDate.js\n",[83,25753,25754,25756,25758,25760],{"class":85,"line":708},[83,25755,24605],{"class":974},[83,25757,24966],{"class":250},[83,25759,24681],{"class":250},[83,25761,25762],{"class":250}," constants\u002F\n",[83,25764,25765,25767,25769,25771],{"class":85,"line":760},[83,25766,24605],{"class":974},[83,25768,24966],{"class":250},[83,25770,25066],{"class":250},[83,25772,25773],{"class":250}," roles.js\n",[83,25775,25776,25778],{"class":85,"line":765},[83,25777,24605],{"class":974},[83,25779,25076],{"class":250},[83,25781,25782,25784,25786],{"class":85,"line":829},[83,25783,24605],{"class":974},[83,25785,24608],{"class":250},[83,25787,25263],{"class":250},[83,25789,25790,25792,25794,25796,25799],{"class":85,"line":863},[83,25791,24605],{"class":974},[83,25793,24966],{"class":250},[83,25795,24681],{"class":250},[83,25797,25798],{"class":250}," index.js",[83,25800,25801],{"class":167},"                # Archivo principal del router que importa las rutas de los módulos\n",[83,25803,25805,25807,25809],{"class":85,"line":25804},44,[83,25806,24605],{"class":974},[83,25808,24966],{"class":250},[83,25810,25811],{"class":167},"                               # (los guards van aquí)\n",[83,25813,25815,25817,25819],{"class":85,"line":25814},45,[83,25816,24605],{"class":974},[83,25818,24608],{"class":250},[83,25820,25311],{"class":250},[83,25822,25824,25826],{"class":85,"line":25823},46,[83,25825,24564],{"class":974},[83,25827,25311],{"class":250},[12,25829,25830,25831,25834],{},"Cada módulo o funcionalidad concentra ",[40,25832,25833],{},"todo lo que necesita en un solo lugar",", lo que simplifica la navegación y facilita el mantenimiento del código. Este enfoque resulta especialmente beneficioso en aplicaciones grandes o complejas.",[12,25836,25837,25838,25841],{},"La carpeta ",[61,25839,25840],{},"shared\u002F"," nos sirve para almacenar componentes, composables, utilidades y constantes que son reutilizables en toda la aplicación (solo ten cuidado de no sobrecargarla).",[12,25843,25844,25845,25848],{},"La base de este enfoque consiste en dividir la aplicación en módulos independientes dentro de ",[61,25846,25847],{},"\u002Fsrc\u002Fmodules",", cada uno con su propia estructura interna.",[2073,25850,25851],{},[12,25852,25853,25854,25859],{},"Al final, la elección depende del tamaño y complejidad de tu proyecto, así como de las ",[40,25855,25856],{},[1887,25857,25858],{},"preferencias de tu equipo",", asi que no hay una única forma correcta de hacerlo. Estos son solo ejemplos para inspirarte.",[29,25861],{},[32,25863,25865],{"id":25864},"entendiendo-como-se-monta-la-app-vue","Entendiendo como se monta la app Vue",[12,25867,25868,25869,25872,25873,624],{},"El punto de entrada de la aplicación Vue en sí, es el archivo ",[61,25870,25871],{},"src\u002Fmain.js",", aquí es donde se inicializa, se configuran los plugins y se monta en el DOM. Si vemos el archivo ",[61,25874,25871],{},[74,25876,25880],{"className":25877,"code":25878,"language":25879,"meta":79,"style":79},"language-javascript shiki shiki-themes vitesse-light vitesse-dark","import '.\u002Fassets\u002Fmain.css';\n\nimport { createApp } from 'vue';\nimport { createPinia } from 'pinia';\n\nimport App from '.\u002FApp.vue';\nimport router from '.\u002Frouter';\n\nconst app = createApp(App);\n\napp.use(createPinia());\napp.use(router);\n\napp.mount('#app');\n","javascript",[61,25881,25882,25896,25900,25925,25947,25951,25969,25987,25991,26012,26016,26034,26049,26053],{"__ignoreMap":79},[83,25883,25884,25886,25888,25891,25893],{"class":85,"line":86},[83,25885,90],{"class":89},[83,25887,4009],{"class":246},[83,25889,25890],{"class":250},".\u002Fassets\u002Fmain.css",[83,25892,961],{"class":246},[83,25894,25895],{"class":132},";\n",[83,25897,25898],{"class":85,"line":103},[83,25899,161],{"emptyLinePlaceholder":160},[83,25901,25902,25904,25907,25910,25913,25916,25918,25921,25923],{"class":85,"line":116},[83,25903,90],{"class":89},[83,25905,25906],{"class":132}," {",[83,25908,25909],{"class":852}," createApp",[83,25911,25912],{"class":132}," }",[83,25914,25915],{"class":89}," from",[83,25917,4009],{"class":246},[83,25919,25920],{"class":250},"vue",[83,25922,961],{"class":246},[83,25924,25895],{"class":132},[83,25926,25927,25929,25931,25934,25936,25938,25940,25943,25945],{"class":85,"line":124},[83,25928,90],{"class":89},[83,25930,25906],{"class":132},[83,25932,25933],{"class":852}," createPinia",[83,25935,25912],{"class":132},[83,25937,25915],{"class":89},[83,25939,4009],{"class":246},[83,25941,25942],{"class":250},"pinia",[83,25944,961],{"class":246},[83,25946,25895],{"class":132},[83,25948,25949],{"class":85,"line":144},[83,25950,161],{"emptyLinePlaceholder":160},[83,25952,25953,25955,25958,25960,25962,25965,25967],{"class":85,"line":157},[83,25954,90],{"class":89},[83,25956,25957],{"class":852}," App",[83,25959,25915],{"class":89},[83,25961,4009],{"class":246},[83,25963,25964],{"class":250},".\u002FApp.vue",[83,25966,961],{"class":246},[83,25968,25895],{"class":132},[83,25970,25971,25973,25976,25978,25980,25983,25985],{"class":85,"line":164},[83,25972,90],{"class":89},[83,25974,25975],{"class":852}," router",[83,25977,25915],{"class":89},[83,25979,4009],{"class":246},[83,25981,25982],{"class":250},".\u002Frouter",[83,25984,961],{"class":246},[83,25986,25895],{"class":132},[83,25988,25989],{"class":85,"line":171},[83,25990,161],{"emptyLinePlaceholder":160},[83,25992,25993,25996,25999,26002,26004,26006,26009],{"class":85,"line":197},[83,25994,25995],{"class":512},"const",[83,25997,25998],{"class":852}," app",[83,26000,26001],{"class":132}," =",[83,26003,25909],{"class":974},[83,26005,187],{"class":132},[83,26007,26008],{"class":852},"App",[83,26010,26011],{"class":132},");\n",[83,26013,26014],{"class":85,"line":212},[83,26015,161],{"emptyLinePlaceholder":160},[83,26017,26018,26021,26023,26026,26028,26031],{"class":85,"line":217},[83,26019,26020],{"class":852},"app",[83,26022,133],{"class":132},[83,26024,26025],{"class":974},"use",[83,26027,187],{"class":132},[83,26029,26030],{"class":974},"createPinia",[83,26032,26033],{"class":132},"());\n",[83,26035,26036,26038,26040,26042,26044,26047],{"class":85,"line":223},[83,26037,26020],{"class":852},[83,26039,133],{"class":132},[83,26041,26025],{"class":974},[83,26043,187],{"class":132},[83,26045,26046],{"class":852},"router",[83,26048,26011],{"class":132},[83,26050,26051],{"class":85,"line":235},[83,26052,161],{"emptyLinePlaceholder":160},[83,26054,26055,26057,26059,26062,26064,26066,26069,26071],{"class":85,"line":279},[83,26056,26020],{"class":852},[83,26058,133],{"class":132},[83,26060,26061],{"class":974},"mount",[83,26063,187],{"class":132},[83,26065,961],{"class":246},[83,26067,26068],{"class":250},"#app",[83,26070,961],{"class":246},[83,26072,26011],{"class":132},[12,26074,26075],{},"Aquí estamos haciendo lo siguiente:",[1406,26077,26078,26085,26094,26099,26105,26115,26122,26128],{},[1362,26079,26080,26081,26084],{},"Importamos los estilos globales desde ",[61,26082,26083],{},"main.css",". Este archivo contiene cualquier estilo que quieras aplicar globalmente.",[1362,26086,26087,26088,1966,26091,26093],{},"Importamos las funciones ",[61,26089,26090],{},"createApp",[61,26092,26030],{}," para crear nuevas instancias de Vue y Pinia.",[1362,26095,26096,26097,133],{},"Importamos el componente raíz ",[61,26098,24901],{},[1362,26100,26101,26102,133],{},"Importamos la configuración de nuestras rutas desde ",[61,26103,26104],{},"src\u002Frouter\u002Findex.js",[1362,26106,26107,26108,26111,26112,26114],{},"Creamos la instancia de la aplicación con ",[61,26109,26110],{},"createApp(App)",", pasando el componente raíz ",[61,26113,26008],{}," como argumento, indicando que este será el punto de partida de nuestra aplicación Vue, básicamente le estamos diciendo a Vue: \"Aquí está el componente principal, toda la aplicación la construirás a partir de él\".",[1362,26116,26117,26118,26121],{},"Usamos ",[61,26119,26120],{},"app.use(createPinia())"," para registrar la instancia de Pinia, habilitando el manejo de estado global en nuestra aplicación.",[1362,26123,26117,26124,26127],{},[61,26125,26126],{},"app.use(router)"," para registrar la instancia de Vue Router y habilitar la navegación entre vistas.",[1362,26129,26130,26131,26133,26134,133],{},"Finalmente, montamos la aplicación Vue en el elemento del DOM con el id ",[61,26132,26020],{}," usando ",[61,26135,26136],{},"app.mount('#app')",[12,26138,26139,26140,26143],{},"Ahora, abre el archivo ",[61,26141,26142],{},"index.html"," ubicado en la raíz del proyecto:",[74,26145,26149],{"className":26146,"code":26147,"language":26148,"meta":79,"style":79},"language-html shiki shiki-themes vitesse-light vitesse-dark","\u003C!DOCTYPE html>\n\u003Chtml lang=\"\">\n  \u003Chead>\n    \u003Cmeta charset=\"UTF-8\" \u002F>\n    \u003Clink rel=\"icon\" href=\"\u002Ffavicon.ico\" \u002F>\n    \u003Cmeta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" \u002F>\n    \u003Ctitle>Vite App\u003C\u002Ftitle>\n  \u003C\u002Fhead>\n  \u003Cbody>\n    \u003Cdiv id=\"app\">\u003C\u002Fdiv>\n    \u003Cscript type=\"module\" src=\"\u002Fsrc\u002Fmain.js\">\u003C\u002Fscript>\n  \u003C\u002Fbody>\n\u003C\u002Fhtml>\n","html",[61,26150,26151,26164,26180,26189,26212,26245,26277,26296,26305,26314,26339,26376,26384],{"__ignoreMap":79},[83,26152,26153,26156,26159,26162],{"class":85,"line":86},[83,26154,26155],{"class":132},"\u003C!",[83,26157,26158],{"class":89},"DOCTYPE",[83,26160,26161],{"class":852}," html",[83,26163,969],{"class":132},[83,26165,26166,26168,26170,26173,26175,26178],{"class":85,"line":103},[83,26167,955],{"class":132},[83,26169,26148],{"class":89},[83,26171,26172],{"class":852}," lang",[83,26174,229],{"class":132},[83,26176,26177],{"class":246},"\"\"",[83,26179,969],{"class":132},[83,26181,26182,26185,26187],{"class":85,"line":116},[83,26183,26184],{"class":132},"  \u003C",[83,26186,871],{"class":89},[83,26188,969],{"class":132},[83,26190,26191,26194,26197,26200,26202,26204,26207,26209],{"class":85,"line":124},[83,26192,26193],{"class":132},"    \u003C",[83,26195,26196],{"class":89},"meta",[83,26198,26199],{"class":852}," charset",[83,26201,229],{"class":132},[83,26203,247],{"class":246},[83,26205,26206],{"class":250},"UTF-8",[83,26208,247],{"class":246},[83,26210,26211],{"class":132}," \u002F>\n",[83,26213,26214,26216,26219,26222,26224,26226,26229,26231,26234,26236,26238,26241,26243],{"class":85,"line":144},[83,26215,26193],{"class":132},[83,26217,26218],{"class":89},"link",[83,26220,26221],{"class":852}," rel",[83,26223,229],{"class":132},[83,26225,247],{"class":246},[83,26227,26228],{"class":250},"icon",[83,26230,247],{"class":246},[83,26232,26233],{"class":852}," href",[83,26235,229],{"class":132},[83,26237,247],{"class":246},[83,26239,26240],{"class":250},"\u002Ffavicon.ico",[83,26242,247],{"class":246},[83,26244,26211],{"class":132},[83,26246,26247,26249,26251,26254,26256,26258,26261,26263,26266,26268,26270,26273,26275],{"class":85,"line":157},[83,26248,26193],{"class":132},[83,26250,26196],{"class":89},[83,26252,26253],{"class":852}," name",[83,26255,229],{"class":132},[83,26257,247],{"class":246},[83,26259,26260],{"class":250},"viewport",[83,26262,247],{"class":246},[83,26264,26265],{"class":852}," content",[83,26267,229],{"class":132},[83,26269,247],{"class":246},[83,26271,26272],{"class":250},"width=device-width, initial-scale=1.0",[83,26274,247],{"class":246},[83,26276,26211],{"class":132},[83,26278,26279,26281,26283,26286,26289,26292,26294],{"class":85,"line":164},[83,26280,26193],{"class":132},[83,26282,1533],{"class":89},[83,26284,26285],{"class":132},">",[83,26287,26288],{"class":93},"Vite App",[83,26290,26291],{"class":132},"\u003C\u002F",[83,26293,1533],{"class":89},[83,26295,969],{"class":132},[83,26297,26298,26301,26303],{"class":85,"line":171},[83,26299,26300],{"class":132},"  \u003C\u002F",[83,26302,871],{"class":89},[83,26304,969],{"class":132},[83,26306,26307,26309,26312],{"class":85,"line":197},[83,26308,26184],{"class":132},[83,26310,26311],{"class":89},"body",[83,26313,969],{"class":132},[83,26315,26316,26318,26321,26324,26326,26328,26330,26332,26335,26337],{"class":85,"line":212},[83,26317,26193],{"class":132},[83,26319,26320],{"class":89},"div",[83,26322,26323],{"class":852}," id",[83,26325,229],{"class":132},[83,26327,247],{"class":246},[83,26329,26020],{"class":250},[83,26331,247],{"class":246},[83,26333,26334],{"class":132},">\u003C\u002F",[83,26336,26320],{"class":89},[83,26338,969],{"class":132},[83,26340,26341,26343,26346,26349,26351,26353,26356,26358,26361,26363,26365,26368,26370,26372,26374],{"class":85,"line":217},[83,26342,26193],{"class":132},[83,26344,26345],{"class":89},"script",[83,26347,26348],{"class":852}," type",[83,26350,229],{"class":132},[83,26352,247],{"class":246},[83,26354,26355],{"class":250},"module",[83,26357,247],{"class":246},[83,26359,26360],{"class":852}," src",[83,26362,229],{"class":132},[83,26364,247],{"class":246},[83,26366,26367],{"class":250},"\u002Fsrc\u002Fmain.js",[83,26369,247],{"class":246},[83,26371,26334],{"class":132},[83,26373,26345],{"class":89},[83,26375,969],{"class":132},[83,26377,26378,26380,26382],{"class":85,"line":223},[83,26379,26300],{"class":132},[83,26381,26311],{"class":89},[83,26383,969],{"class":132},[83,26385,26386,26388,26390],{"class":85,"line":235},[83,26387,26291],{"class":132},[83,26389,26148],{"class":89},[83,26391,969],{"class":132},[12,26393,26394,26395,26398,26399,26401,26402,26405,26406,26408],{},"Aquí vemos que el archivo HTML tiene un ",[61,26396,26397],{},"\u003Cdiv>"," con el id ",[61,26400,26020],{},", que es donde Vue montará nuestra aplicación. El ",[61,26403,26404],{},"\u003Cscript>"," que le sigue carga nuestro archivo ",[61,26407,24907],{},", que es donde inicializamos todo.",[12,26410,26411,26412,624],{},"Abre el archivo ",[61,26413,26414],{},"src\u002FApp.vue",[74,26416,26419],{"className":26417,"code":26418,"language":25920,"meta":79,"style":79},"language-vue shiki shiki-themes vitesse-light vitesse-dark","\u003Cscript setup>\nimport { RouterLink, RouterView } from 'vue-router';\nimport HelloWorld from '.\u002Fcomponents\u002FHelloWorld.vue';\n\u003C\u002Fscript>\n\n\u003Ctemplate>\n  \u003Cheader>\n    \u003Cimg alt=\"Vue logo\" class=\"logo\" src=\"@\u002Fassets\u002Flogo.svg\" width=\"125\" height=\"125\" \u002F>\n\n    \u003Cdiv class=\"wrapper\">\n      \u003CHelloWorld msg=\"You did it!\" \u002F>\n\n      \u003Cnav>\n        \u003CRouterLink to=\"\u002F\">Home\u003C\u002FRouterLink>\n        \u003CRouterLink to=\"\u002Fabout\">About\u003C\u002FRouterLink>\n      \u003C\u002Fnav>\n    \u003C\u002Fdiv>\n  \u003C\u002Fheader>\n\n  \u003CRouterView \u002F>\n\u003C\u002Ftemplate>\n\n\u003Cstyle scoped>\n\u002F* Estilos CSS *\u002F\n\u003C\u002Fstyle>\n",[61,26420,26421,26432,26459,26477,26485,26489,26498,26507,26573,26577,26596,26618,26622,26631,26660,26688,26697,26706,26714,26718,26727,26735,26739,26750,26755],{"__ignoreMap":79},[83,26422,26423,26425,26427,26430],{"class":85,"line":86},[83,26424,955],{"class":132},[83,26426,26345],{"class":89},[83,26428,26429],{"class":852}," setup",[83,26431,969],{"class":132},[83,26433,26434,26436,26438,26441,26443,26446,26448,26450,26452,26455,26457],{"class":85,"line":103},[83,26435,90],{"class":89},[83,26437,25906],{"class":132},[83,26439,26440],{"class":852}," RouterLink",[83,26442,256],{"class":132},[83,26444,26445],{"class":852}," RouterView",[83,26447,25912],{"class":132},[83,26449,25915],{"class":89},[83,26451,4009],{"class":246},[83,26453,26454],{"class":250},"vue-router",[83,26456,961],{"class":246},[83,26458,25895],{"class":132},[83,26460,26461,26463,26466,26468,26470,26473,26475],{"class":85,"line":116},[83,26462,90],{"class":89},[83,26464,26465],{"class":852}," HelloWorld",[83,26467,25915],{"class":89},[83,26469,4009],{"class":246},[83,26471,26472],{"class":250},".\u002Fcomponents\u002FHelloWorld.vue",[83,26474,961],{"class":246},[83,26476,25895],{"class":132},[83,26478,26479,26481,26483],{"class":85,"line":124},[83,26480,26291],{"class":132},[83,26482,26345],{"class":89},[83,26484,969],{"class":132},[83,26486,26487],{"class":85,"line":144},[83,26488,161],{"emptyLinePlaceholder":160},[83,26490,26491,26493,26496],{"class":85,"line":157},[83,26492,955],{"class":132},[83,26494,26495],{"class":89},"template",[83,26497,969],{"class":132},[83,26499,26500,26502,26505],{"class":85,"line":164},[83,26501,26184],{"class":132},[83,26503,26504],{"class":89},"header",[83,26506,969],{"class":132},[83,26508,26509,26511,26513,26516,26518,26520,26523,26525,26528,26530,26532,26535,26537,26539,26541,26543,26546,26548,26551,26553,26555,26558,26560,26563,26565,26567,26569,26571],{"class":85,"line":171},[83,26510,26193],{"class":132},[83,26512,1882],{"class":89},[83,26514,26515],{"class":852}," alt",[83,26517,229],{"class":132},[83,26519,247],{"class":246},[83,26521,26522],{"class":250},"Vue logo",[83,26524,247],{"class":246},[83,26526,26527],{"class":852}," class",[83,26529,229],{"class":132},[83,26531,247],{"class":246},[83,26533,26534],{"class":250},"logo",[83,26536,247],{"class":246},[83,26538,26360],{"class":852},[83,26540,229],{"class":132},[83,26542,247],{"class":246},[83,26544,26545],{"class":250},"@\u002Fassets\u002Flogo.svg",[83,26547,247],{"class":246},[83,26549,26550],{"class":852}," width",[83,26552,229],{"class":132},[83,26554,247],{"class":246},[83,26556,26557],{"class":250},"125",[83,26559,247],{"class":246},[83,26561,26562],{"class":852}," height",[83,26564,229],{"class":132},[83,26566,247],{"class":246},[83,26568,26557],{"class":250},[83,26570,247],{"class":246},[83,26572,26211],{"class":132},[83,26574,26575],{"class":85,"line":197},[83,26576,161],{"emptyLinePlaceholder":160},[83,26578,26579,26581,26583,26585,26587,26589,26592,26594],{"class":85,"line":212},[83,26580,26193],{"class":132},[83,26582,26320],{"class":89},[83,26584,26527],{"class":852},[83,26586,229],{"class":132},[83,26588,247],{"class":246},[83,26590,26591],{"class":250},"wrapper",[83,26593,247],{"class":246},[83,26595,969],{"class":132},[83,26597,26598,26601,26604,26607,26609,26611,26614,26616],{"class":85,"line":217},[83,26599,26600],{"class":132},"      \u003C",[83,26602,26603],{"class":89},"HelloWorld",[83,26605,26606],{"class":852}," msg",[83,26608,229],{"class":132},[83,26610,247],{"class":246},[83,26612,26613],{"class":250},"You did it!",[83,26615,247],{"class":246},[83,26617,26211],{"class":132},[83,26619,26620],{"class":85,"line":223},[83,26621,161],{"emptyLinePlaceholder":160},[83,26623,26624,26626,26629],{"class":85,"line":235},[83,26625,26600],{"class":132},[83,26627,26628],{"class":89},"nav",[83,26630,969],{"class":132},[83,26632,26633,26636,26639,26641,26643,26645,26647,26649,26651,26654,26656,26658],{"class":85,"line":279},[83,26634,26635],{"class":132},"        \u003C",[83,26637,26638],{"class":89},"RouterLink",[83,26640,987],{"class":852},[83,26642,229],{"class":132},[83,26644,247],{"class":246},[83,26646,68],{"class":250},[83,26648,247],{"class":246},[83,26650,26285],{"class":132},[83,26652,26653],{"class":93},"Home",[83,26655,26291],{"class":132},[83,26657,26638],{"class":89},[83,26659,969],{"class":132},[83,26661,26662,26664,26666,26668,26670,26672,26675,26677,26679,26682,26684,26686],{"class":85,"line":290},[83,26663,26635],{"class":132},[83,26665,26638],{"class":89},[83,26667,987],{"class":852},[83,26669,229],{"class":132},[83,26671,247],{"class":246},[83,26673,26674],{"class":250},"\u002Fabout",[83,26676,247],{"class":246},[83,26678,26285],{"class":132},[83,26680,26681],{"class":93},"About",[83,26683,26291],{"class":132},[83,26685,26638],{"class":89},[83,26687,969],{"class":132},[83,26689,26690,26693,26695],{"class":85,"line":295},[83,26691,26692],{"class":132},"      \u003C\u002F",[83,26694,26628],{"class":89},[83,26696,969],{"class":132},[83,26698,26699,26702,26704],{"class":85,"line":319},[83,26700,26701],{"class":132},"    \u003C\u002F",[83,26703,26320],{"class":89},[83,26705,969],{"class":132},[83,26707,26708,26710,26712],{"class":85,"line":357},[83,26709,26300],{"class":132},[83,26711,26504],{"class":89},[83,26713,969],{"class":132},[83,26715,26716],{"class":85,"line":392},[83,26717,161],{"emptyLinePlaceholder":160},[83,26719,26720,26722,26725],{"class":85,"line":421},[83,26721,26184],{"class":132},[83,26723,26724],{"class":89},"RouterView",[83,26726,26211],{"class":132},[83,26728,26729,26731,26733],{"class":85,"line":456},[83,26730,26291],{"class":132},[83,26732,26495],{"class":89},[83,26734,969],{"class":132},[83,26736,26737],{"class":85,"line":477},[83,26738,161],{"emptyLinePlaceholder":160},[83,26740,26741,26743,26745,26748],{"class":85,"line":483},[83,26742,955],{"class":132},[83,26744,4374],{"class":89},[83,26746,26747],{"class":852}," scoped",[83,26749,969],{"class":132},[83,26751,26752],{"class":85,"line":489},[83,26753,26754],{"class":167},"\u002F* Estilos CSS *\u002F\n",[83,26756,26757,26759,26761],{"class":85,"line":495},[83,26758,26291],{"class":132},[83,26760,4374],{"class":89},[83,26762,969],{"class":132},[12,26764,26765,26766,26768,26769,26771,26772,26775],{},"Aquí vemos que ",[61,26767,24901],{}," contiene un encabezado (header) con un logo, un componente ",[61,26770,26603],{},", y un menú de navegación con enlaces a las rutas definidas. El ",[61,26773,26774],{},"\u003CRouterView \u002F>"," es donde se renderizarán las vistas correspondientes según la ruta actual, gracias a Vue Router.",[12,26777,26778,26779,624],{},"Exploremos la configuración del router. Abre el archivo ",[61,26780,26104],{},[74,26782,26784],{"className":25877,"code":26783,"language":25879,"meta":79,"style":79},"import { createRouter, createWebHistory } from 'vue-router';\nimport HomeView from '..\u002Fviews\u002FHomeView.vue';\n\nconst router = createRouter({\n  history: createWebHistory(import.meta.env.BASE_URL),\n  routes: [\n    {\n      path: '\u002F',\n      name: 'home',\n      component: HomeView,\n    },\n    {\n      path: '\u002Fabout',\n      name: 'about',\n      \u002F* Esta ruta usa lazy loading *\u002F\n      component: () => import('..\u002Fviews\u002FAboutView.vue'),\n    },\n  ],\n});\n\nexport default router;\n",[61,26785,26786,26812,26830,26834,26846,26876,26886,26891,26906,26922,26933,26938,26942,26956,26971,26976,27002,27006,27011,27016,27020],{"__ignoreMap":79},[83,26787,26788,26790,26792,26795,26797,26800,26802,26804,26806,26808,26810],{"class":85,"line":86},[83,26789,90],{"class":89},[83,26791,25906],{"class":132},[83,26793,26794],{"class":852}," createRouter",[83,26796,256],{"class":132},[83,26798,26799],{"class":852}," createWebHistory",[83,26801,25912],{"class":132},[83,26803,25915],{"class":89},[83,26805,4009],{"class":246},[83,26807,26454],{"class":250},[83,26809,961],{"class":246},[83,26811,25895],{"class":132},[83,26813,26814,26816,26819,26821,26823,26826,26828],{"class":85,"line":103},[83,26815,90],{"class":89},[83,26817,26818],{"class":852}," HomeView",[83,26820,25915],{"class":89},[83,26822,4009],{"class":246},[83,26824,26825],{"class":250},"..\u002Fviews\u002FHomeView.vue",[83,26827,961],{"class":246},[83,26829,25895],{"class":132},[83,26831,26832],{"class":85,"line":116},[83,26833,161],{"emptyLinePlaceholder":160},[83,26835,26836,26838,26840,26842,26844],{"class":85,"line":124},[83,26837,25995],{"class":512},[83,26839,25975],{"class":852},[83,26841,26001],{"class":132},[83,26843,26794],{"class":974},[83,26845,4122],{"class":132},[83,26847,26848,26851,26853,26855,26857,26859,26861,26863,26865,26868,26870,26873],{"class":85,"line":144},[83,26849,26850],{"class":307},"  history",[83,26852,624],{"class":132},[83,26854,26799],{"class":974},[83,26856,187],{"class":132},[83,26858,90],{"class":89},[83,26860,133],{"class":132},[83,26862,26196],{"class":307},[83,26864,133],{"class":132},[83,26866,26867],{"class":852},"env",[83,26869,133],{"class":132},[83,26871,26872],{"class":852},"BASE_URL",[83,26874,26875],{"class":132},"),\n",[83,26877,26878,26881,26883],{"class":85,"line":157},[83,26879,26880],{"class":307},"  routes",[83,26882,624],{"class":132},[83,26884,26885],{"class":132}," [\n",[83,26887,26888],{"class":85,"line":164},[83,26889,26890],{"class":132},"    {\n",[83,26892,26893,26896,26898,26900,26902,26904],{"class":85,"line":171},[83,26894,26895],{"class":307},"      path",[83,26897,624],{"class":132},[83,26899,4009],{"class":246},[83,26901,68],{"class":250},[83,26903,961],{"class":246},[83,26905,4143],{"class":132},[83,26907,26908,26911,26913,26915,26918,26920],{"class":85,"line":197},[83,26909,26910],{"class":307},"      name",[83,26912,624],{"class":132},[83,26914,4009],{"class":246},[83,26916,26917],{"class":250},"home",[83,26919,961],{"class":246},[83,26921,4143],{"class":132},[83,26923,26924,26927,26929,26931],{"class":85,"line":212},[83,26925,26926],{"class":307},"      component",[83,26928,624],{"class":132},[83,26930,26818],{"class":852},[83,26932,4143],{"class":132},[83,26934,26935],{"class":85,"line":217},[83,26936,26937],{"class":132},"    },\n",[83,26939,26940],{"class":85,"line":223},[83,26941,26890],{"class":132},[83,26943,26944,26946,26948,26950,26952,26954],{"class":85,"line":235},[83,26945,26895],{"class":307},[83,26947,624],{"class":132},[83,26949,4009],{"class":246},[83,26951,26674],{"class":250},[83,26953,961],{"class":246},[83,26955,4143],{"class":132},[83,26957,26958,26960,26962,26964,26967,26969],{"class":85,"line":279},[83,26959,26910],{"class":307},[83,26961,624],{"class":132},[83,26963,4009],{"class":246},[83,26965,26966],{"class":250},"about",[83,26968,961],{"class":246},[83,26970,4143],{"class":132},[83,26972,26973],{"class":85,"line":290},[83,26974,26975],{"class":167},"      \u002F* Esta ruta usa lazy loading *\u002F\n",[83,26977,26978,26980,26982,26985,26988,26991,26993,26995,26998,27000],{"class":85,"line":295},[83,26979,26926],{"class":974},[83,26981,624],{"class":132},[83,26983,26984],{"class":132}," ()",[83,26986,26987],{"class":132}," =>",[83,26989,26990],{"class":512}," import",[83,26992,187],{"class":132},[83,26994,961],{"class":246},[83,26996,26997],{"class":250},"..\u002Fviews\u002FAboutView.vue",[83,26999,961],{"class":246},[83,27001,26875],{"class":132},[83,27003,27004],{"class":85,"line":319},[83,27005,26937],{"class":132},[83,27007,27008],{"class":85,"line":357},[83,27009,27010],{"class":132},"  ],\n",[83,27012,27013],{"class":85,"line":392},[83,27014,27015],{"class":132},"});\n",[83,27017,27018],{"class":85,"line":421},[83,27019,161],{"emptyLinePlaceholder":160},[83,27021,27022,27025,27028,27030],{"class":85,"line":456},[83,27023,27024],{"class":89},"export",[83,27026,27027],{"class":89}," default",[83,27029,25975],{"class":852},[83,27031,25895],{"class":132},[12,27033,27034,27035,27038,27039,27042,27043,27045,27046,27048,27049,27051,27052,27054,27055,27060],{},"Aquí estamos importando las funciones necesarias de Vue Router y definiendo una ruta básica para la vista ",[61,27036,27037],{},"HomeView"," y otra para ",[61,27040,27041],{},"AboutView",". La ruta ",[61,27044,68],{}," renderiza ",[61,27047,27037],{},", y la ruta ",[61,27050,26674],{}," carga ",[61,27053,27041],{}," utilizando carga diferida (",[19,27056,27059],{"href":27057,"target":17502,"rel":27058},"https:\u002F\u002Fmedium.com\u002F@drewcauchi\u002Flazy-loading-in-vue-js-bb32018d2c2d",[17504,17505],"lazy loading",").",[12,27062,27063],{},"Repasemos el flujo completo:",[1406,27065,27066,27074,27083],{},[1362,27067,27068,27069,27071,27072,133],{},"El archivo ",[61,27070,26142],{}," es lo que el navegador nos muestra, y lo primero que hace es cargar ",[61,27073,24907],{},[1362,27075,27076,27077,27079,27080,27082],{},"En ",[61,27078,24907],{},", se crea la aplicación Vue con ",[61,27081,24901],{}," como componente raíz (a parte de importar estilos, configurar Pinia, Vue Router y otras configuraciones).",[1362,27084,27085,27087,27088,27090],{},[61,27086,24901],{}," define la estructura principal de la aplicación (como un layout principal) y utiliza ",[61,27089,26774],{}," para renderizar las vistas según la ruta actual.",[12,27092,27093,27097],{},[1882,27094],{"alt":27095,"src":27096},"Flujo de una app Vue","\u002Fblog\u002Fgetting-started-vue-vite\u002Fes\u002Fexplaining-vue-app.webp",[1887,27098,27095],{},[12,27100,27101,27102,27104,27105,27107],{},"Esto quiere decir que todo lo que veas dentro de ",[61,27103,24901],{}," estará siempre presente (como el header y el menú de navegación), mientras que el contenido principal se mostrará dentro de ",[61,27106,26774],{}," y cambiará dependiendo de la ruta actual, gracias a nuestro router.",[12,27109,27110,27111,27113,27114,133],{},"Normalmente, en aplicaciones más complejas, ",[61,27112,24901],{}," también contendrá otros elementos comunes como un footer, barras laterales, modales globales, etc.\nY cuando se necesita, se crean layouts específicos para diferentes módulos de la aplicación, por ejemplo, un layout para las vistas de administración y otro para las vistas públicas como el inicio de sesión. Puedes explorar más en ",[19,27115,27118],{"href":27116,"target":17502,"rel":27117},"https:\u002F\u002Fvueschool.io\u002Farticles\u002Fvuejs-tutorials\u002Fcomposing-layouts-with-vue-router\u002F",[17504,17505],"este recurso de Vue School",[29,27120],{},[12,27122,27123],{},"A este punto ya tenemos una idea clara de cómo se estructura y monta una aplicación Vue 3 con Vite. Puedes comenzar a explorar y modificar los componentes, vistas y rutas para familiarizarte más con el framework. Ahora seguiremos explorando otros conceptos y herramientas importantes del ecosistema.",[29,27125],{},[32,27127,27129],{"id":27128},"pinia-para-manejo-de-estado-global","Pinia para manejo de estado global",[12,27131,27132],{},"Pinia nos sirve para manejar el estado global de nuestra aplicación: datos que deben ser accesibles desde cualquier parte de la aplicación, datos que necesitamos compartir entre múltiples componentes o vistas.",[12,27134,27135],{},"Por ejemplo, cuando necesitamos tener acceso a la información del usuario autenticado en diferentes partes de la app, o si queremos manejar un carrito de compras que pueda ser consultado desde distintos componentes.",[12,27137,27138,27139,624],{},"Veamos un ejemplo básico. Crea el archivo ",[61,27140,27141],{},"src\u002Fstore\u002Fauth.store.js",[74,27143,27145],{"className":25877,"code":27144,"language":25879,"meta":79,"style":79},"import { defineStore } from 'pinia';\nexport const useAuthStore = defineStore('auth', {\n  state: () => ({\n    user: null,\n    token: null,\n  }),\n  actions: {\n    login(userData, token) {\n      this.user = userData;\n      this.token = token;\n    },\n    logout() {\n      this.user = null;\n      this.token = null;\n    },\n  },\n});\n",[61,27146,27147,27168,27196,27210,27222,27233,27238,27247,27266,27283,27298,27302,27312,27326,27340,27344,27349],{"__ignoreMap":79},[83,27148,27149,27151,27153,27156,27158,27160,27162,27164,27166],{"class":85,"line":86},[83,27150,90],{"class":89},[83,27152,25906],{"class":132},[83,27154,27155],{"class":852}," defineStore",[83,27157,25912],{"class":132},[83,27159,25915],{"class":89},[83,27161,4009],{"class":246},[83,27163,25942],{"class":250},[83,27165,961],{"class":246},[83,27167,25895],{"class":132},[83,27169,27170,27172,27175,27178,27180,27182,27184,27186,27189,27191,27193],{"class":85,"line":103},[83,27171,27024],{"class":89},[83,27173,27174],{"class":512}," const",[83,27176,27177],{"class":852}," useAuthStore",[83,27179,26001],{"class":132},[83,27181,27155],{"class":974},[83,27183,187],{"class":132},[83,27185,961],{"class":246},[83,27187,27188],{"class":250},"auth",[83,27190,961],{"class":246},[83,27192,256],{"class":132},[83,27194,27195],{"class":132}," {\n",[83,27197,27198,27201,27203,27205,27207],{"class":85,"line":116},[83,27199,27200],{"class":974},"  state",[83,27202,624],{"class":132},[83,27204,26984],{"class":132},[83,27206,26987],{"class":132},[83,27208,27209],{"class":132}," ({\n",[83,27211,27212,27215,27217,27220],{"class":85,"line":124},[83,27213,27214],{"class":307},"    user",[83,27216,624],{"class":132},[83,27218,27219],{"class":512}," null",[83,27221,4143],{"class":132},[83,27223,27224,27227,27229,27231],{"class":85,"line":144},[83,27225,27226],{"class":307},"    token",[83,27228,624],{"class":132},[83,27230,27219],{"class":512},[83,27232,4143],{"class":132},[83,27234,27235],{"class":85,"line":157},[83,27236,27237],{"class":132},"  }),\n",[83,27239,27240,27243,27245],{"class":85,"line":164},[83,27241,27242],{"class":307},"  actions",[83,27244,624],{"class":132},[83,27246,27195],{"class":132},[83,27248,27249,27252,27254,27257,27259,27262,27264],{"class":85,"line":171},[83,27250,27251],{"class":974},"    login",[83,27253,187],{"class":132},[83,27255,27256],{"class":852},"userData",[83,27258,256],{"class":132},[83,27260,27261],{"class":852}," token",[83,27263,534],{"class":132},[83,27265,27195],{"class":132},[83,27267,27268,27271,27273,27276,27278,27281],{"class":85,"line":197},[83,27269,27270],{"class":1020},"      this",[83,27272,133],{"class":132},[83,27274,27275],{"class":852},"user",[83,27277,26001],{"class":132},[83,27279,27280],{"class":852}," userData",[83,27282,25895],{"class":132},[83,27284,27285,27287,27289,27292,27294,27296],{"class":85,"line":212},[83,27286,27270],{"class":1020},[83,27288,133],{"class":132},[83,27290,27291],{"class":852},"token",[83,27293,26001],{"class":132},[83,27295,27261],{"class":852},[83,27297,25895],{"class":132},[83,27299,27300],{"class":85,"line":217},[83,27301,26937],{"class":132},[83,27303,27304,27307,27310],{"class":85,"line":223},[83,27305,27306],{"class":974},"    logout",[83,27308,27309],{"class":132},"()",[83,27311,27195],{"class":132},[83,27313,27314,27316,27318,27320,27322,27324],{"class":85,"line":235},[83,27315,27270],{"class":1020},[83,27317,133],{"class":132},[83,27319,27275],{"class":852},[83,27321,26001],{"class":132},[83,27323,27219],{"class":512},[83,27325,25895],{"class":132},[83,27327,27328,27330,27332,27334,27336,27338],{"class":85,"line":279},[83,27329,27270],{"class":1020},[83,27331,133],{"class":132},[83,27333,27291],{"class":852},[83,27335,26001],{"class":132},[83,27337,27219],{"class":512},[83,27339,25895],{"class":132},[83,27341,27342],{"class":85,"line":290},[83,27343,26937],{"class":132},[83,27345,27346],{"class":85,"line":295},[83,27347,27348],{"class":132},"  },\n",[83,27350,27351],{"class":85,"line":319},[83,27352,27015],{"class":132},[12,27354,27355,27356,27358,27359,1966,27361,27363,27364,624],{},"Aquí estamos definiendo una store llamada ",[61,27357,27188],{}," que tiene un estado con las propiedades ",[61,27360,27275],{},[61,27362,27291],{},", y dos acciones para iniciar sesión y cerrar sesión.\nAhora, veamos cómo usar esta store en un componente. Crea un componente Vue, por ejemplo ",[61,27365,27366],{},"src\u002Fcomponents\u002FAuth.vue",[74,27368,27370],{"className":26417,"code":27369,"language":25920,"meta":79,"style":79},"\u003Ctemplate>\n  \u003Cdiv>\n    \u003Cdiv v-if=\"authStore.user\">\n      \u003Cp>Welcome, {{ authStore.user.name }}!\u003C\u002Fp>\n      \u003Cbutton @click=\"logout\">Logout\u003C\u002Fbutton>\n    \u003C\u002Fdiv>\n    \u003Cdiv v-else>\n      \u003Cbutton @click=\"login\">Login\u003C\u002Fbutton>\n    \u003C\u002Fdiv>\n  \u003C\u002Fdiv>\n\u003C\u002Ftemplate>\n\u003Cscript setup>\nimport { useAuthStore } from '..\u002Fstore\u002Fauth.store';\nconst authStore = useAuthStore();\nconst login = () => {\n  \u002F\u002F Simulamos un inicio de sesión\n  const userData = { name: 'John Doe', email: 'john.doe@example.com' };\n  const token = 'fake-jwt-token';\n  authStore.login(userData, token);\n};\n\nconst logout = () => {\n  authStore.logout();\n};\n\u003C\u002Fscript>\n",[61,27371,27372,27380,27388,27408,27425,27455,27463,27474,27502,27510,27518,27526,27536,27557,27571,27586,27591,27630,27647,27666,27671,27675,27690,27700,27704],{"__ignoreMap":79},[83,27373,27374,27376,27378],{"class":85,"line":86},[83,27375,955],{"class":132},[83,27377,26495],{"class":89},[83,27379,969],{"class":132},[83,27381,27382,27384,27386],{"class":85,"line":103},[83,27383,26184],{"class":132},[83,27385,26320],{"class":89},[83,27387,969],{"class":132},[83,27389,27390,27392,27394,27397,27399,27401,27404,27406],{"class":85,"line":116},[83,27391,26193],{"class":132},[83,27393,26320],{"class":89},[83,27395,27396],{"class":852}," v-if",[83,27398,229],{"class":132},[83,27400,247],{"class":246},[83,27402,27403],{"class":250},"authStore.user",[83,27405,247],{"class":246},[83,27407,969],{"class":132},[83,27409,27410,27412,27414,27416,27419,27421,27423],{"class":85,"line":124},[83,27411,26600],{"class":132},[83,27413,12],{"class":89},[83,27415,26285],{"class":132},[83,27417,27418],{"class":93},"Welcome, {{ authStore.user.name }}!",[83,27420,26291],{"class":132},[83,27422,12],{"class":89},[83,27424,969],{"class":132},[83,27426,27427,27429,27432,27435,27437,27439,27442,27444,27446,27449,27451,27453],{"class":85,"line":144},[83,27428,26600],{"class":132},[83,27430,27431],{"class":89},"button",[83,27433,27434],{"class":852}," @click",[83,27436,229],{"class":132},[83,27438,247],{"class":246},[83,27440,27441],{"class":250},"logout",[83,27443,247],{"class":246},[83,27445,26285],{"class":132},[83,27447,27448],{"class":93},"Logout",[83,27450,26291],{"class":132},[83,27452,27431],{"class":89},[83,27454,969],{"class":132},[83,27456,27457,27459,27461],{"class":85,"line":157},[83,27458,26701],{"class":132},[83,27460,26320],{"class":89},[83,27462,969],{"class":132},[83,27464,27465,27467,27469,27472],{"class":85,"line":164},[83,27466,26193],{"class":132},[83,27468,26320],{"class":89},[83,27470,27471],{"class":852}," v-else",[83,27473,969],{"class":132},[83,27475,27476,27478,27480,27482,27484,27486,27489,27491,27493,27496,27498,27500],{"class":85,"line":171},[83,27477,26600],{"class":132},[83,27479,27431],{"class":89},[83,27481,27434],{"class":852},[83,27483,229],{"class":132},[83,27485,247],{"class":246},[83,27487,27488],{"class":250},"login",[83,27490,247],{"class":246},[83,27492,26285],{"class":132},[83,27494,27495],{"class":93},"Login",[83,27497,26291],{"class":132},[83,27499,27431],{"class":89},[83,27501,969],{"class":132},[83,27503,27504,27506,27508],{"class":85,"line":197},[83,27505,26701],{"class":132},[83,27507,26320],{"class":89},[83,27509,969],{"class":132},[83,27511,27512,27514,27516],{"class":85,"line":212},[83,27513,26300],{"class":132},[83,27515,26320],{"class":89},[83,27517,969],{"class":132},[83,27519,27520,27522,27524],{"class":85,"line":217},[83,27521,26291],{"class":132},[83,27523,26495],{"class":89},[83,27525,969],{"class":132},[83,27527,27528,27530,27532,27534],{"class":85,"line":223},[83,27529,955],{"class":132},[83,27531,26345],{"class":89},[83,27533,26429],{"class":852},[83,27535,969],{"class":132},[83,27537,27538,27540,27542,27544,27546,27548,27550,27553,27555],{"class":85,"line":235},[83,27539,90],{"class":89},[83,27541,25906],{"class":132},[83,27543,27177],{"class":852},[83,27545,25912],{"class":132},[83,27547,25915],{"class":89},[83,27549,4009],{"class":246},[83,27551,27552],{"class":250},"..\u002Fstore\u002Fauth.store",[83,27554,961],{"class":246},[83,27556,25895],{"class":132},[83,27558,27559,27561,27564,27566,27568],{"class":85,"line":279},[83,27560,25995],{"class":512},[83,27562,27563],{"class":852}," authStore",[83,27565,26001],{"class":132},[83,27567,27177],{"class":974},[83,27569,27570],{"class":132},"();\n",[83,27572,27573,27575,27578,27580,27582,27584],{"class":85,"line":290},[83,27574,25995],{"class":512},[83,27576,27577],{"class":974}," login",[83,27579,26001],{"class":132},[83,27581,26984],{"class":132},[83,27583,26987],{"class":132},[83,27585,27195],{"class":132},[83,27587,27588],{"class":85,"line":295},[83,27589,27590],{"class":167},"  \u002F\u002F Simulamos un inicio de sesión\n",[83,27592,27593,27596,27598,27600,27602,27604,27606,27608,27611,27613,27615,27618,27620,27622,27625,27627],{"class":85,"line":319},[83,27594,27595],{"class":512},"  const",[83,27597,27280],{"class":852},[83,27599,26001],{"class":132},[83,27601,25906],{"class":132},[83,27603,26253],{"class":307},[83,27605,624],{"class":132},[83,27607,4009],{"class":246},[83,27609,27610],{"class":250},"John Doe",[83,27612,961],{"class":246},[83,27614,256],{"class":132},[83,27616,27617],{"class":307}," email",[83,27619,624],{"class":132},[83,27621,4009],{"class":246},[83,27623,27624],{"class":250},"john.doe@example.com",[83,27626,961],{"class":246},[83,27628,27629],{"class":132}," };\n",[83,27631,27632,27634,27636,27638,27640,27643,27645],{"class":85,"line":357},[83,27633,27595],{"class":512},[83,27635,27261],{"class":852},[83,27637,26001],{"class":132},[83,27639,4009],{"class":246},[83,27641,27642],{"class":250},"fake-jwt-token",[83,27644,961],{"class":246},[83,27646,25895],{"class":132},[83,27648,27649,27652,27654,27656,27658,27660,27662,27664],{"class":85,"line":392},[83,27650,27651],{"class":852},"  authStore",[83,27653,133],{"class":132},[83,27655,27488],{"class":974},[83,27657,187],{"class":132},[83,27659,27256],{"class":852},[83,27661,256],{"class":132},[83,27663,27261],{"class":852},[83,27665,26011],{"class":132},[83,27667,27668],{"class":85,"line":421},[83,27669,27670],{"class":132},"};\n",[83,27672,27673],{"class":85,"line":456},[83,27674,161],{"emptyLinePlaceholder":160},[83,27676,27677,27679,27682,27684,27686,27688],{"class":85,"line":477},[83,27678,25995],{"class":512},[83,27680,27681],{"class":974}," logout",[83,27683,26001],{"class":132},[83,27685,26984],{"class":132},[83,27687,26987],{"class":132},[83,27689,27195],{"class":132},[83,27691,27692,27694,27696,27698],{"class":85,"line":483},[83,27693,27651],{"class":852},[83,27695,133],{"class":132},[83,27697,27441],{"class":974},[83,27699,27570],{"class":132},[83,27701,27702],{"class":85,"line":489},[83,27703,27670],{"class":132},[83,27705,27706,27708,27710],{"class":85,"line":495},[83,27707,26291],{"class":132},[83,27709,26345],{"class":89},[83,27711,969],{"class":132},[12,27713,27714,27715,27718,27719,27721,27722,1966,27724,27726],{},"Aquí estamos importando la store ",[61,27716,27717],{},"useAuthStore"," y usándola para acceder al estado ",[61,27720,27275],{}," y las acciones ",[61,27723,27488],{},[61,27725,27441],{},".\nGracias a Pinia, el estado del usuario se mantiene consistente en todas partes, y cualquier cambio (como iniciar o cerrar sesión) se refleja automáticamente en todos los componentes que usan esta store.",[12,27728,27729],{},"Algunos casos reales de uso:",[1359,27731,27732,27738,27744],{},[1362,27733,27734,27737],{},[40,27735,27736],{},"Autenticación de usuarios",": Creas una store para manejar el estado del usuario autenticado, con datos como el token, nombre, roles, etc. Puedes crear acciones para iniciar sesión, cerrar sesión y actualizar la información del usuario.",[1362,27739,27740,27743],{},[40,27741,27742],{},"Carrito de compras",": Creas una store para manejar los productos en el carrito, con acciones para agregar, eliminar y actualizar productos. Este estado puede ser accedido desde cualquier parte de la aplicación, como la página de productos y la página del carrito.",[1362,27745,27746,27749],{},[40,27747,27748],{},"Preferencias de usuario",": Creas una store para manejar las preferencias del usuario, como el tema (claro\u002Foscuro), idioma, etc. Puedes crear acciones para actualizar estas preferencias y reflejarlas en toda la aplicación.",[12,27751,27752,27753,133],{},"Puedes explorar más sobre Pinia en la ",[19,27754,24539],{"href":24878,"target":17502,"rel":27755},[17504,17505],[29,27757],{},[32,27759,27761],{"id":27760},"composables","Composables",[12,27763,27764],{},"Los composables son funciones reutilizables que encapsulan lógica específica, con estado, y pueden ser usados entre diferentes componentes.",[12,27766,27767,27768,27771],{},"Nos permiten organizar mejor nuestro código, promoviendo la reutilización y la separación de responsabilidades. Normalmente toda lógica con estado la pondríamos dentro de un ",[61,27769,27770],{},"\u003Cscript setup>"," en un componente Vue, pero si esa lógica es algo que podría ser útil en varios componentes, podemos extraerla a un composable.",[12,27773,27774,27775,624],{},"Veamos un ejemplo bastante básico. Crea un archivo llamado ",[61,27776,27777],{},"src\u002Fcomposables\u002FuseClipboard.js",[74,27779,27781],{"className":25877,"code":27780,"language":25879,"meta":79,"style":79},"import { ref } from 'vue';\n\nexport function useClipboard() {\n  const copied = ref(false);\n\n  const copyToClipboard = async (text) => {\n    try {\n      await navigator.clipboard.writeText(text);\n      copied.value = true;\n      setTimeout(() => {\n        copied.value = false;\n      }, 2000);\n    } catch (error) {\n      console.error('Failed to copy: ', error);\n    }\n  };\n\n  return {\n    copied,\n    copyToClipboard,\n  };\n}\n",[61,27782,27783,27804,27808,27822,27839,27843,27865,27872,27896,27913,27925,27941,27951,27968,27993,27998,28003,28007,28014,28021,28028,28032],{"__ignoreMap":79},[83,27784,27785,27787,27789,27792,27794,27796,27798,27800,27802],{"class":85,"line":86},[83,27786,90],{"class":89},[83,27788,25906],{"class":132},[83,27790,27791],{"class":852}," ref",[83,27793,25912],{"class":132},[83,27795,25915],{"class":89},[83,27797,4009],{"class":246},[83,27799,25920],{"class":250},[83,27801,961],{"class":246},[83,27803,25895],{"class":132},[83,27805,27806],{"class":85,"line":103},[83,27807,161],{"emptyLinePlaceholder":160},[83,27809,27810,27812,27815,27818,27820],{"class":85,"line":116},[83,27811,27024],{"class":89},[83,27813,27814],{"class":512}," function",[83,27816,27817],{"class":974}," useClipboard",[83,27819,27309],{"class":132},[83,27821,27195],{"class":132},[83,27823,27824,27826,27829,27831,27833,27835,27837],{"class":85,"line":124},[83,27825,27595],{"class":512},[83,27827,27828],{"class":852}," copied",[83,27830,26001],{"class":132},[83,27832,27791],{"class":974},[83,27834,187],{"class":132},[83,27836,6169],{"class":89},[83,27838,26011],{"class":132},[83,27840,27841],{"class":85,"line":144},[83,27842,161],{"emptyLinePlaceholder":160},[83,27844,27845,27847,27850,27852,27855,27857,27859,27861,27863],{"class":85,"line":157},[83,27846,27595],{"class":512},[83,27848,27849],{"class":974}," copyToClipboard",[83,27851,26001],{"class":132},[83,27853,27854],{"class":512}," async",[83,27856,23230],{"class":132},[83,27858,2235],{"class":852},[83,27860,534],{"class":132},[83,27862,26987],{"class":132},[83,27864,27195],{"class":132},[83,27866,27867,27870],{"class":85,"line":164},[83,27868,27869],{"class":89},"    try",[83,27871,27195],{"class":132},[83,27873,27874,27877,27880,27882,27885,27887,27890,27892,27894],{"class":85,"line":171},[83,27875,27876],{"class":89},"      await",[83,27878,27879],{"class":852}," navigator",[83,27881,133],{"class":132},[83,27883,27884],{"class":852},"clipboard",[83,27886,133],{"class":132},[83,27888,27889],{"class":974},"writeText",[83,27891,187],{"class":132},[83,27893,2235],{"class":852},[83,27895,26011],{"class":132},[83,27897,27898,27901,27903,27906,27908,27911],{"class":85,"line":197},[83,27899,27900],{"class":852},"      copied",[83,27902,133],{"class":132},[83,27904,27905],{"class":852},"value",[83,27907,26001],{"class":132},[83,27909,27910],{"class":89}," true",[83,27912,25895],{"class":132},[83,27914,27915,27918,27921,27923],{"class":85,"line":212},[83,27916,27917],{"class":974},"      setTimeout",[83,27919,27920],{"class":132},"(()",[83,27922,26987],{"class":132},[83,27924,27195],{"class":132},[83,27926,27927,27930,27932,27934,27936,27939],{"class":85,"line":217},[83,27928,27929],{"class":852},"        copied",[83,27931,133],{"class":132},[83,27933,27905],{"class":852},[83,27935,26001],{"class":132},[83,27937,27938],{"class":89}," false",[83,27940,25895],{"class":132},[83,27942,27943,27946,27949],{"class":85,"line":223},[83,27944,27945],{"class":132},"      },",[83,27947,27948],{"class":190}," 2000",[83,27950,26011],{"class":132},[83,27952,27953,27956,27959,27961,27964,27966],{"class":85,"line":235},[83,27954,27955],{"class":132},"    }",[83,27957,27958],{"class":89}," catch",[83,27960,23230],{"class":132},[83,27962,27963],{"class":852},"error",[83,27965,534],{"class":132},[83,27967,27195],{"class":132},[83,27969,27970,27973,27975,27977,27979,27981,27984,27986,27988,27991],{"class":85,"line":279},[83,27971,27972],{"class":852},"      console",[83,27974,133],{"class":132},[83,27976,27963],{"class":974},[83,27978,187],{"class":132},[83,27980,961],{"class":246},[83,27982,27983],{"class":250},"Failed to copy: ",[83,27985,961],{"class":246},[83,27987,256],{"class":132},[83,27989,27990],{"class":852}," error",[83,27992,26011],{"class":132},[83,27994,27995],{"class":85,"line":290},[83,27996,27997],{"class":132},"    }\n",[83,27999,28000],{"class":85,"line":295},[83,28001,28002],{"class":132},"  };\n",[83,28004,28005],{"class":85,"line":319},[83,28006,161],{"emptyLinePlaceholder":160},[83,28008,28009,28012],{"class":85,"line":357},[83,28010,28011],{"class":89},"  return",[83,28013,27195],{"class":132},[83,28015,28016,28019],{"class":85,"line":392},[83,28017,28018],{"class":852},"    copied",[83,28020,4143],{"class":132},[83,28022,28023,28026],{"class":85,"line":421},[83,28024,28025],{"class":852},"    copyToClipboard",[83,28027,4143],{"class":132},[83,28029,28030],{"class":85,"line":456},[83,28031,28002],{"class":132},[83,28033,28034],{"class":85,"line":477},[83,28035,28036],{"class":132},"}\n",[12,28038,28039,28040,28043,28044,28047,28048,28051],{},"Aquí estamos definiendo un composable llamado ",[61,28041,28042],{},"useClipboard"," que proporciona una función para copiar texto al portapapeles y un estado ",[40,28045,28046],{},"reactivo"," ",[61,28049,28050],{},"copied"," que indica si el texto fue copiado exitosamente.",[12,28053,28054,28055,624],{},"Al implementarlo podríamos tener algo como esto. Crea un componente llamado ",[61,28056,28057],{},"src\u002Fcomponents\u002FClipboardExample.vue",[74,28059,28061],{"className":26417,"code":28060,"language":25920,"meta":79,"style":79},"\u003Ctemplate>\n  \u003Cdiv>\n    \u003Cinput v-model=\"textToCopy\" placeholder=\"Type something to copy\" \u002F>\n    \u003Cbutton @click=\"copyToClipboard(textToCopy)\">Copy to Clipboard\u003C\u002Fbutton>\n    \u003Cp v-if=\"copied\">Text copied!\u003C\u002Fp>\n  \u003C\u002Fdiv>\n\u003C\u002Ftemplate>\n\u003Cscript setup>\nimport { ref } from 'vue';\nimport { useClipboard } from '..\u002Fcomposables\u002FuseClipboard';\nconst { copied, copyToClipboard } = useClipboard();\nconst textToCopy = ref('');\n\u003C\u002Fscript>\n",[61,28062,28063,28071,28079,28112,28140,28167,28175,28183,28193,28213,28234,28254,28272],{"__ignoreMap":79},[83,28064,28065,28067,28069],{"class":85,"line":86},[83,28066,955],{"class":132},[83,28068,26495],{"class":89},[83,28070,969],{"class":132},[83,28072,28073,28075,28077],{"class":85,"line":103},[83,28074,26184],{"class":132},[83,28076,26320],{"class":89},[83,28078,969],{"class":132},[83,28080,28081,28083,28086,28089,28091,28093,28096,28098,28101,28103,28105,28108,28110],{"class":85,"line":116},[83,28082,26193],{"class":132},[83,28084,28085],{"class":89},"input",[83,28087,28088],{"class":852}," v-model",[83,28090,229],{"class":132},[83,28092,247],{"class":246},[83,28094,28095],{"class":250},"textToCopy",[83,28097,247],{"class":246},[83,28099,28100],{"class":852}," placeholder",[83,28102,229],{"class":132},[83,28104,247],{"class":246},[83,28106,28107],{"class":250},"Type something to copy",[83,28109,247],{"class":246},[83,28111,26211],{"class":132},[83,28113,28114,28116,28118,28120,28122,28124,28127,28129,28131,28134,28136,28138],{"class":85,"line":124},[83,28115,26193],{"class":132},[83,28117,27431],{"class":89},[83,28119,27434],{"class":852},[83,28121,229],{"class":132},[83,28123,247],{"class":246},[83,28125,28126],{"class":250},"copyToClipboard(textToCopy)",[83,28128,247],{"class":246},[83,28130,26285],{"class":132},[83,28132,28133],{"class":93},"Copy to Clipboard",[83,28135,26291],{"class":132},[83,28137,27431],{"class":89},[83,28139,969],{"class":132},[83,28141,28142,28144,28146,28148,28150,28152,28154,28156,28158,28161,28163,28165],{"class":85,"line":144},[83,28143,26193],{"class":132},[83,28145,12],{"class":89},[83,28147,27396],{"class":852},[83,28149,229],{"class":132},[83,28151,247],{"class":246},[83,28153,28050],{"class":250},[83,28155,247],{"class":246},[83,28157,26285],{"class":132},[83,28159,28160],{"class":93},"Text copied!",[83,28162,26291],{"class":132},[83,28164,12],{"class":89},[83,28166,969],{"class":132},[83,28168,28169,28171,28173],{"class":85,"line":157},[83,28170,26300],{"class":132},[83,28172,26320],{"class":89},[83,28174,969],{"class":132},[83,28176,28177,28179,28181],{"class":85,"line":164},[83,28178,26291],{"class":132},[83,28180,26495],{"class":89},[83,28182,969],{"class":132},[83,28184,28185,28187,28189,28191],{"class":85,"line":171},[83,28186,955],{"class":132},[83,28188,26345],{"class":89},[83,28190,26429],{"class":852},[83,28192,969],{"class":132},[83,28194,28195,28197,28199,28201,28203,28205,28207,28209,28211],{"class":85,"line":197},[83,28196,90],{"class":89},[83,28198,25906],{"class":132},[83,28200,27791],{"class":852},[83,28202,25912],{"class":132},[83,28204,25915],{"class":89},[83,28206,4009],{"class":246},[83,28208,25920],{"class":250},[83,28210,961],{"class":246},[83,28212,25895],{"class":132},[83,28214,28215,28217,28219,28221,28223,28225,28227,28230,28232],{"class":85,"line":212},[83,28216,90],{"class":89},[83,28218,25906],{"class":132},[83,28220,27817],{"class":852},[83,28222,25912],{"class":132},[83,28224,25915],{"class":89},[83,28226,4009],{"class":246},[83,28228,28229],{"class":250},"..\u002Fcomposables\u002FuseClipboard",[83,28231,961],{"class":246},[83,28233,25895],{"class":132},[83,28235,28236,28238,28240,28242,28244,28246,28248,28250,28252],{"class":85,"line":217},[83,28237,25995],{"class":512},[83,28239,25906],{"class":132},[83,28241,27828],{"class":852},[83,28243,256],{"class":132},[83,28245,27849],{"class":852},[83,28247,25912],{"class":132},[83,28249,26001],{"class":132},[83,28251,27817],{"class":974},[83,28253,27570],{"class":132},[83,28255,28256,28258,28261,28263,28265,28267,28270],{"class":85,"line":223},[83,28257,25995],{"class":512},[83,28259,28260],{"class":852}," textToCopy",[83,28262,26001],{"class":132},[83,28264,27791],{"class":974},[83,28266,187],{"class":132},[83,28268,28269],{"class":246},"''",[83,28271,26011],{"class":132},[83,28273,28274,28276,28278],{"class":85,"line":235},[83,28275,26291],{"class":132},[83,28277,26345],{"class":89},[83,28279,969],{"class":132},[12,28281,28282,28283,28285,28286,28288],{},"Y luego importa este componente en ",[61,28284,24901],{}," y añádelo debajo del componente ",[61,28287,26603],{}," para probarlo:",[74,28290,28292],{"className":26417,"code":28291,"language":25920,"meta":79,"style":79},"\u003Cscript setup>\nimport { RouterLink, RouterView } from 'vue-router';\nimport HelloWorld from '.\u002Fcomponents\u002FHelloWorld.vue';\nimport ClipboardExample from '.\u002Fcomponents\u002FClipboardExample.vue';\n\u003C\u002Fscript>\n\n\u003Ctemplate>\n  \u003Cheader>\n    \u003Cimg alt=\"Vue logo\" class=\"logo\" src=\"@\u002Fassets\u002Flogo.svg\" width=\"125\" height=\"125\" \u002F>\n\n    \u003Cdiv class=\"wrapper\">\n      \u003CHelloWorld msg=\"You did it!\" \u002F>\n      \u003CClipboardExample \u002F>\n      \u003C!-- Aquí -->\n      \u003Cnav>\n        \u003CRouterLink to=\"\u002F\">Home\u003C\u002FRouterLink>\n        \u003CRouterLink to=\"\u002Fabout\">About\u003C\u002FRouterLink>\n      \u003C\u002Fnav>\n    \u003C\u002Fdiv>\n  \u003C\u002Fheader>\n\n  \u003CRouterView \u002F>\n\u003C\u002Ftemplate>\n",[61,28293,28294,28304,28328,28344,28362,28370,28374,28382,28390,28448,28452,28470,28488,28497,28502,28510,28536,28562,28570,28578,28586,28590,28598],{"__ignoreMap":79},[83,28295,28296,28298,28300,28302],{"class":85,"line":86},[83,28297,955],{"class":132},[83,28299,26345],{"class":89},[83,28301,26429],{"class":852},[83,28303,969],{"class":132},[83,28305,28306,28308,28310,28312,28314,28316,28318,28320,28322,28324,28326],{"class":85,"line":103},[83,28307,90],{"class":89},[83,28309,25906],{"class":132},[83,28311,26440],{"class":852},[83,28313,256],{"class":132},[83,28315,26445],{"class":852},[83,28317,25912],{"class":132},[83,28319,25915],{"class":89},[83,28321,4009],{"class":246},[83,28323,26454],{"class":250},[83,28325,961],{"class":246},[83,28327,25895],{"class":132},[83,28329,28330,28332,28334,28336,28338,28340,28342],{"class":85,"line":116},[83,28331,90],{"class":89},[83,28333,26465],{"class":852},[83,28335,25915],{"class":89},[83,28337,4009],{"class":246},[83,28339,26472],{"class":250},[83,28341,961],{"class":246},[83,28343,25895],{"class":132},[83,28345,28346,28348,28351,28353,28355,28358,28360],{"class":85,"line":124},[83,28347,90],{"class":89},[83,28349,28350],{"class":852}," ClipboardExample",[83,28352,25915],{"class":89},[83,28354,4009],{"class":246},[83,28356,28357],{"class":250},".\u002Fcomponents\u002FClipboardExample.vue",[83,28359,961],{"class":246},[83,28361,25895],{"class":132},[83,28363,28364,28366,28368],{"class":85,"line":144},[83,28365,26291],{"class":132},[83,28367,26345],{"class":89},[83,28369,969],{"class":132},[83,28371,28372],{"class":85,"line":157},[83,28373,161],{"emptyLinePlaceholder":160},[83,28375,28376,28378,28380],{"class":85,"line":164},[83,28377,955],{"class":132},[83,28379,26495],{"class":89},[83,28381,969],{"class":132},[83,28383,28384,28386,28388],{"class":85,"line":171},[83,28385,26184],{"class":132},[83,28387,26504],{"class":89},[83,28389,969],{"class":132},[83,28391,28392,28394,28396,28398,28400,28402,28404,28406,28408,28410,28412,28414,28416,28418,28420,28422,28424,28426,28428,28430,28432,28434,28436,28438,28440,28442,28444,28446],{"class":85,"line":197},[83,28393,26193],{"class":132},[83,28395,1882],{"class":89},[83,28397,26515],{"class":852},[83,28399,229],{"class":132},[83,28401,247],{"class":246},[83,28403,26522],{"class":250},[83,28405,247],{"class":246},[83,28407,26527],{"class":852},[83,28409,229],{"class":132},[83,28411,247],{"class":246},[83,28413,26534],{"class":250},[83,28415,247],{"class":246},[83,28417,26360],{"class":852},[83,28419,229],{"class":132},[83,28421,247],{"class":246},[83,28423,26545],{"class":250},[83,28425,247],{"class":246},[83,28427,26550],{"class":852},[83,28429,229],{"class":132},[83,28431,247],{"class":246},[83,28433,26557],{"class":250},[83,28435,247],{"class":246},[83,28437,26562],{"class":852},[83,28439,229],{"class":132},[83,28441,247],{"class":246},[83,28443,26557],{"class":250},[83,28445,247],{"class":246},[83,28447,26211],{"class":132},[83,28449,28450],{"class":85,"line":212},[83,28451,161],{"emptyLinePlaceholder":160},[83,28453,28454,28456,28458,28460,28462,28464,28466,28468],{"class":85,"line":217},[83,28455,26193],{"class":132},[83,28457,26320],{"class":89},[83,28459,26527],{"class":852},[83,28461,229],{"class":132},[83,28463,247],{"class":246},[83,28465,26591],{"class":250},[83,28467,247],{"class":246},[83,28469,969],{"class":132},[83,28471,28472,28474,28476,28478,28480,28482,28484,28486],{"class":85,"line":223},[83,28473,26600],{"class":132},[83,28475,26603],{"class":89},[83,28477,26606],{"class":852},[83,28479,229],{"class":132},[83,28481,247],{"class":246},[83,28483,26613],{"class":250},[83,28485,247],{"class":246},[83,28487,26211],{"class":132},[83,28489,28490,28492,28495],{"class":85,"line":235},[83,28491,26600],{"class":132},[83,28493,28494],{"class":89},"ClipboardExample",[83,28496,26211],{"class":132},[83,28498,28499],{"class":85,"line":279},[83,28500,28501],{"class":167},"      \u003C!-- Aquí -->\n",[83,28503,28504,28506,28508],{"class":85,"line":290},[83,28505,26600],{"class":132},[83,28507,26628],{"class":89},[83,28509,969],{"class":132},[83,28511,28512,28514,28516,28518,28520,28522,28524,28526,28528,28530,28532,28534],{"class":85,"line":295},[83,28513,26635],{"class":132},[83,28515,26638],{"class":89},[83,28517,987],{"class":852},[83,28519,229],{"class":132},[83,28521,247],{"class":246},[83,28523,68],{"class":250},[83,28525,247],{"class":246},[83,28527,26285],{"class":132},[83,28529,26653],{"class":93},[83,28531,26291],{"class":132},[83,28533,26638],{"class":89},[83,28535,969],{"class":132},[83,28537,28538,28540,28542,28544,28546,28548,28550,28552,28554,28556,28558,28560],{"class":85,"line":319},[83,28539,26635],{"class":132},[83,28541,26638],{"class":89},[83,28543,987],{"class":852},[83,28545,229],{"class":132},[83,28547,247],{"class":246},[83,28549,26674],{"class":250},[83,28551,247],{"class":246},[83,28553,26285],{"class":132},[83,28555,26681],{"class":93},[83,28557,26291],{"class":132},[83,28559,26638],{"class":89},[83,28561,969],{"class":132},[83,28563,28564,28566,28568],{"class":85,"line":357},[83,28565,26692],{"class":132},[83,28567,26628],{"class":89},[83,28569,969],{"class":132},[83,28571,28572,28574,28576],{"class":85,"line":392},[83,28573,26701],{"class":132},[83,28575,26320],{"class":89},[83,28577,969],{"class":132},[83,28579,28580,28582,28584],{"class":85,"line":421},[83,28581,26300],{"class":132},[83,28583,26504],{"class":89},[83,28585,969],{"class":132},[83,28587,28588],{"class":85,"line":456},[83,28589,161],{"emptyLinePlaceholder":160},[83,28591,28592,28594,28596],{"class":85,"line":477},[83,28593,26184],{"class":132},[83,28595,26724],{"class":89},[83,28597,26211],{"class":132},[83,28599,28600,28602,28604],{"class":85,"line":483},[83,28601,26291],{"class":132},[83,28603,26495],{"class":89},[83,28605,969],{"class":132},[12,28607,28608,28609,28611],{},"El estado ",[61,28610,28050],{}," nos permite mostrar un mensaje cuando el texto ha sido copiado exitosamente.",[12,28613,28614],{},"¿Que logramos con esto?",[1359,28616,28617,28626,28632],{},[1362,28618,28619,28622,28623,28625],{},[40,28620,28621],{},"Reutilización",": Podemos usar ",[61,28624,28042],{}," en cualquier componente que necesite funcionalidad de copiar al portapapeles, sin duplicar código.",[1362,28627,28628,28631],{},[40,28629,28630],{},"Organización",": La lógica relacionada con el portapapeles está encapsulada en un solo lugar.",[1362,28633,28634,28637],{},[40,28635,28636],{},"Mantenimiento",": Si necesitamos cambiar la forma en que copiamos al portapapeles, solo tenemos que modificar el composable, no todos los componentes que lo usan.",[53,28639,28641],{"id":28640},"cuál-es-la-diferencia-entre-un-composable-y-una-store-de-pinia","¿Cuál es la diferencia entre un composable y una store de Pinia?",[12,28643,28644,28647,28648,28651],{},[40,28645,28646],{},"Estado global vs estado local",": Las stores de Pinia están diseñadas para manejar un estado global en la aplicación, datos que deben ser ",[40,28649,28650],{},"accesibles y compartidos"," desde cualquier parte.",[12,28653,28654,28655,28658,28659,28661],{},"Los composables, por otro lado, manejan lógica y estado que puede ser reutilizado en múltiples componentes, pero que ",[40,28656,28657],{},"nada de eso es compartido",". Por ejemplo, si tengo varios componentes que necesitan funcionalidad para copiar al portapapeles (y que necesitan algún control de estado), usaría un composable, y el estado ",[61,28660,28050],{}," sería local en cada instancia del composable. En cambio, si necesito saber en varios lugares si actualmente se ha realizado una copia al portapapeles a nivel de aplicación, usaría una store de Pinia, porque aquí si se darían cuenta todos los componentes y todos podrían reaccionar a ese cambio.",[12,28663,28664,28665,28667,28668,28670],{},"Pongámoslo como un ejemplo: gracias a la variable ",[61,28666,28050],{}," puedo mostrar algo dentro del mismo componente, como el mensaje de \"Texto copiado\", ahora, si quisiera que por ejemplo el layout de mi aplicación muestre un ícono en la barra de navegación cada vez que se copie algo al portapapeles, entonces sería mejor que utilizara una store de Pinia para manejar ese estado globalmente, así al copiar desde mi componente ",[61,28669,28494],{},", el layout también se daría cuenta del cambio y podría mostrar el ícono.",[53,28672,28674],{"id":28673},"cuál-es-la-diferencia-entre-un-composable-y-un-archivo-de-utilidades-utils","¿Cuál es la diferencia entre un composable y un archivo de utilidades (utils)?",[12,28676,28677,28678,28680],{},"Las funciones de utilidades son generalmente más simples y no tienen estado, reciben entradas (algunas) y devuelven salidas sin efectos secundarios. Por ejemplo, si no necesitáramos el estado ",[61,28679,28050],{}," y solo quisiéramos una función para copiar texto, podríamos crear una simple función de utilidad en lugar de un composable:",[74,28682,28684],{"className":25877,"code":28683,"language":25879,"meta":79,"style":79},"export function copyToClipboard(text) {\n  return navigator.clipboard.writeText(text);\n}\n",[61,28685,28686,28702,28722],{"__ignoreMap":79},[83,28687,28688,28690,28692,28694,28696,28698,28700],{"class":85,"line":86},[83,28689,27024],{"class":89},[83,28691,27814],{"class":512},[83,28693,27849],{"class":974},[83,28695,187],{"class":132},[83,28697,2235],{"class":852},[83,28699,534],{"class":132},[83,28701,27195],{"class":132},[83,28703,28704,28706,28708,28710,28712,28714,28716,28718,28720],{"class":85,"line":103},[83,28705,28011],{"class":89},[83,28707,27879],{"class":852},[83,28709,133],{"class":132},[83,28711,27884],{"class":852},[83,28713,133],{"class":132},[83,28715,27889],{"class":974},[83,28717,187],{"class":132},[83,28719,2235],{"class":852},[83,28721,26011],{"class":132},[83,28723,28724],{"class":85,"line":116},[83,28725,28036],{"class":132},[12,28727,28728],{},"Lecturas recomendadas:",[1359,28730,28731,28738,28745],{},[1362,28732,28733],{},[19,28734,28737],{"href":28735,"target":17502,"rel":28736},"https:\u002F\u002Fvuejs.org\u002Fguide\u002Freusability\u002Fcomposables.html",[17504,17505],"Composables - Vue.js Documentation",[1362,28739,28740],{},[19,28741,28744],{"href":28742,"target":17502,"rel":28743},"https:\u002F\u002Fdev.to\u002Fjacobandrewsky\u002Fgood-practices-and-design-patterns-for-vue-composables-24lk",[17504,17505],"Good Practices and Design Patterns for Vue Composables",[1362,28746,28747],{},[19,28748,28751],{"href":28749,"target":17502,"rel":28750},"https:\u002F\u002Frobconery.com\u002Ffrontend\u002Fwhat-should-be-a-plugin-vs-a-composable-vs-a-store-in-nuxt\u002F",[17504,17505],"What should be a Plugin vs a Composable vs a Store in Nuxt",[53,28753,28755],{"id":28754},"vueuse","VueUse",[12,28757,28758,28762],{},[19,28759,28755],{"href":28760,"target":17502,"rel":28761},"https:\u002F\u002Fvueuse.org\u002F",[17504,17505]," es una colección de composables para Vue 3. Proporciona una amplia gama de funcionalidades listas para usar, desde manejo de estado hasta interacciones con el DOM y APIs del navegador. Puedes explorar la documentación oficial para ver todos los composables disponibles y cómo usarlos en tus proyectos.",[12,28764,28765,28768],{},[1882,28766],{"alt":28755,"src":28767},"\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fvue-use.webp",[1887,28769,28755],{},[12,28771,28772],{},"Algunos ejemplos populares de composables en VueUse incluyen:",[1359,28774,28775,28781,28787,28793,28799],{},[1362,28776,28777,28780],{},[61,28778,28779],{},"useBreakpoints",": para poder manejar breakpoints en tu aplicación y ayudar con el diseño responsivo.",[1362,28782,28783,28786],{},[61,28784,28785],{},"useFetch",": para realizar solicitudes HTTP de manera sencilla.",[1362,28788,28789,28792],{},[61,28790,28791],{},"useLocalStorage",": para sincronizar datos con el almacenamiento local del navegador.",[1362,28794,28795,28798],{},[61,28796,28797],{},"useDark",": para manejar temas oscuros y claros en la aplicación.",[1362,28800,28801,28803],{},[61,28802,28042],{},": para copiar texto al portapapeles (similar al que creamos antes).",[12,28805,28806],{},"Es una colección muy útil que puede ahorrarte tiempo si necesitas alguna de estas funcionalidades.\nSolo ten cuidado de no sobrecargar tu proyecto con dependencias innecesarias, instala solo lo que realmente vayas a usar y solo si realmente necesitas una librería para ella.",[29,28808],{},[32,28810,28812],{"id":28811},"eslint-y-prettier","ESLint y Prettier",[12,28814,28815,28816,28819],{},"Acostúmbrate a usar ",[40,28817,28818],{},"ESLint",", es demasiado útil para mantener la calidad del código y evitar errores comunes.\nLa configuración generada por Vite es un buen punto de partida, pero siempre recomiendo personalizarla.",[12,28821,28822,28823,28827,28828,133],{},"Puedes explorar las reglas disponibles en la documentación oficial ",[19,28824,28818],{"href":28825,"target":17502,"rel":28826},"https:\u002F\u002Feslint.org\u002Fdocs\u002Frules\u002F",[17504,17505]," y de ",[19,28829,28832],{"href":28830,"target":17502,"rel":28831},"https:\u002F\u002Feslint.vuejs.org\u002Frules\u002F",[17504,17505],"eslint-plugin-vue",[12,28834,28835],{},"Todas las reglas pueden ser configuradas como \"off\", \"warn\" o \"error\", dependiendo de la severidad que quieras asignarles:",[74,28837,28841],{"className":28838,"code":28839,"language":28840,"meta":79,"style":79},"language-js shiki shiki-themes vitesse-light vitesse-dark","\"no-console\": \"warn\", \u002F\u002F Muestra una advertencia si se usa console.log\n\"eqeqeq\": \"error\", \u002F\u002F Fuerza el uso de === y !== en lugar de == y !=\n\"vue\u002Fmulti-word-component-names\": \"off\", \u002F\u002F Desactiva la regla que obliga a usar nombres de componentes con múltiples palabras\n","js",[61,28842,28843,28866,28888],{"__ignoreMap":79},[83,28844,28845,28847,28850,28852,28854,28856,28859,28861,28863],{"class":85,"line":86},[83,28846,247],{"class":246},[83,28848,28849],{"class":250},"no-console",[83,28851,247],{"class":246},[83,28853,4932],{"class":93},[83,28855,247],{"class":246},[83,28857,28858],{"class":250},"warn",[83,28860,247],{"class":246},[83,28862,256],{"class":132},[83,28864,28865],{"class":167}," \u002F\u002F Muestra una advertencia si se usa console.log\n",[83,28867,28868,28870,28873,28875,28877,28879,28881,28883,28885],{"class":85,"line":103},[83,28869,247],{"class":246},[83,28871,28872],{"class":250},"eqeqeq",[83,28874,247],{"class":246},[83,28876,4932],{"class":93},[83,28878,247],{"class":246},[83,28880,27963],{"class":250},[83,28882,247],{"class":246},[83,28884,256],{"class":132},[83,28886,28887],{"class":167}," \u002F\u002F Fuerza el uso de === y !== en lugar de == y !=\n",[83,28889,28890,28892,28895,28897,28899,28901,28904,28906,28908],{"class":85,"line":116},[83,28891,247],{"class":246},[83,28893,28894],{"class":250},"vue\u002Fmulti-word-component-names",[83,28896,247],{"class":246},[83,28898,4932],{"class":93},[83,28900,247],{"class":246},[83,28902,28903],{"class":250},"off",[83,28905,247],{"class":246},[83,28907,256],{"class":132},[83,28909,28910],{"class":167}," \u002F\u002F Desactiva la regla que obliga a usar nombres de componentes con múltiples palabras\n",[12,28912,28913,28914,28917,28918,133],{},"En el proyecto que creamos, puedes usar el comando ",[61,28915,28916],{},"npm run lint"," para revisar todo tu código según la configuración del archivo ",[61,28919,28920],{},"eslint.config.js",[12,28922,28923,28926],{},[40,28924,28925],{},"Sobre Prettier",", existe cierto debate sobre su uso, a mucha gente no le gusta porque puede imponer un estilo que no les agrada, así que pruébalo, explóralo y úsalo solo si te sientes cómodo con él.\nEn lugar de Prettier, para intentar siempre mantener un estilo consistente, puedes usar alternativas como EditorConfig, las propias reglas de ESLint o la configuración del editor de código que estés usando.",[12,28928,28929],{},"Si usas algunas de estas herramientas puedes explorar sus extensiones:",[1359,28931,28932,28939,28946],{},[1362,28933,28934],{},[19,28935,28938],{"href":28936,"target":17502,"rel":28937},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=dbaeumer.vscode-eslint",[17504,17505],"ESLint extension for VS Code",[1362,28940,28941],{},[19,28942,28945],{"href":28943,"target":17502,"rel":28944},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=esbenp.prettier-vscode",[17504,17505],"Prettier - Code formatter",[1362,28947,28948],{},[19,28949,28952],{"href":28950,"target":17502,"rel":28951},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=EditorConfig.EditorConfig",[17504,17505],"EditorConfig for VS Code",[29,28954],{},[32,28956,28958],{"id":28957},"extra-instalando-tailwind-css-v4","EXTRA: Instalando Tailwind CSS v4",[12,28960,28961,28962,28967],{},"CSS puro está más que bien, puede lograr resultados increíbles (a veces incluso ",[19,28963,28966],{"href":28964,"target":17502,"rel":28965},"https:\u002F\u002Fgithub.com\u002Fyou-dont-need\u002FYou-Dont-Need-JavaScript",[17504,17505],"sin necesitar JavaScript","), pero un opción que tienes para acelerar tu desarrollo y mantener un estilo consistente es Tailwind CSS.",[12,28969,28970,28971,28976],{},"Siguiendo los pasos oficiales de la ",[19,28972,28975],{"href":28973,"target":17502,"rel":28974},"https:\u002F\u002Ftailwindcss.com\u002Fdocs\u002Finstallation\u002Fusing-vite",[17504,17505],"documentación de Tailwind CSS",", instalemos Tailwind CSS v4 en nuestro proyecto Vue con Vite.",[12,28978,28979],{},"Primero (estando dentro de la carpeta del proyecto), instala Tailwind CSS y su plugin para Vite:",[74,28981,28983],{"className":24218,"code":28982,"language":24220,"meta":79,"style":79},"npm install tailwindcss @tailwindcss\u002Fvite\n",[61,28984,28985],{"__ignoreMap":79},[83,28986,28987,28989,28992,28995],{"class":85,"line":86},[83,28988,24156],{"class":974},[83,28990,28991],{"class":250}," install",[83,28993,28994],{"class":250}," tailwindcss",[83,28996,28997],{"class":250}," @tailwindcss\u002Fvite\n",[12,28999,29000,29001,624],{},"Luego, agregamos el plugin a nuestro archivo ",[61,29002,29003],{},"vite.config.js",[74,29005,29007],{"className":25877,"code":29006,"language":25879,"meta":79,"style":79},"import { fileURLToPath, URL } from 'node:url';\n\nimport { defineConfig } from 'vite';\nimport vue from '@vitejs\u002Fplugin-vue';\nimport vueDevTools from 'vite-plugin-vue-devtools';\nimport tailwindcss from '@tailwindcss\u002Fvite'; \u002F\u002F Importamos el plugin\n\n\u002F\u002F https:\u002F\u002Fvite.dev\u002Fconfig\u002F\nexport default defineConfig({\n  plugins: [\n    vue(),\n    vueDevTools(),\n    tailwindcss(), \u002F\u002F Agregamos a la configuración de Vite\n  ],\n  resolve: {\n    alias: {\n      '@': fileURLToPath(new URL('.\u002Fsrc', import.meta.url)),\n    },\n  },\n});\n",[61,29008,29009,29036,29040,29062,29080,29098,29119,29123,29128,29138,29147,29155,29162,29172,29176,29185,29194,29240,29244,29248],{"__ignoreMap":79},[83,29010,29011,29013,29015,29018,29020,29023,29025,29027,29029,29032,29034],{"class":85,"line":86},[83,29012,90],{"class":89},[83,29014,25906],{"class":132},[83,29016,29017],{"class":852}," fileURLToPath",[83,29019,256],{"class":132},[83,29021,29022],{"class":852}," URL",[83,29024,25912],{"class":132},[83,29026,25915],{"class":89},[83,29028,4009],{"class":246},[83,29030,29031],{"class":250},"node:url",[83,29033,961],{"class":246},[83,29035,25895],{"class":132},[83,29037,29038],{"class":85,"line":103},[83,29039,161],{"emptyLinePlaceholder":160},[83,29041,29042,29044,29046,29049,29051,29053,29055,29058,29060],{"class":85,"line":116},[83,29043,90],{"class":89},[83,29045,25906],{"class":132},[83,29047,29048],{"class":852}," defineConfig",[83,29050,25912],{"class":132},[83,29052,25915],{"class":89},[83,29054,4009],{"class":246},[83,29056,29057],{"class":250},"vite",[83,29059,961],{"class":246},[83,29061,25895],{"class":132},[83,29063,29064,29066,29069,29071,29073,29076,29078],{"class":85,"line":124},[83,29065,90],{"class":89},[83,29067,29068],{"class":852}," vue",[83,29070,25915],{"class":89},[83,29072,4009],{"class":246},[83,29074,29075],{"class":250},"@vitejs\u002Fplugin-vue",[83,29077,961],{"class":246},[83,29079,25895],{"class":132},[83,29081,29082,29084,29087,29089,29091,29094,29096],{"class":85,"line":144},[83,29083,90],{"class":89},[83,29085,29086],{"class":852}," vueDevTools",[83,29088,25915],{"class":89},[83,29090,4009],{"class":246},[83,29092,29093],{"class":250},"vite-plugin-vue-devtools",[83,29095,961],{"class":246},[83,29097,25895],{"class":132},[83,29099,29100,29102,29104,29106,29108,29111,29113,29116],{"class":85,"line":157},[83,29101,90],{"class":89},[83,29103,28994],{"class":852},[83,29105,25915],{"class":89},[83,29107,4009],{"class":246},[83,29109,29110],{"class":250},"@tailwindcss\u002Fvite",[83,29112,961],{"class":246},[83,29114,29115],{"class":132},";",[83,29117,29118],{"class":167}," \u002F\u002F Importamos el plugin\n",[83,29120,29121],{"class":85,"line":164},[83,29122,161],{"emptyLinePlaceholder":160},[83,29124,29125],{"class":85,"line":171},[83,29126,29127],{"class":167},"\u002F\u002F https:\u002F\u002Fvite.dev\u002Fconfig\u002F\n",[83,29129,29130,29132,29134,29136],{"class":85,"line":197},[83,29131,27024],{"class":89},[83,29133,27027],{"class":89},[83,29135,29048],{"class":974},[83,29137,4122],{"class":132},[83,29139,29140,29143,29145],{"class":85,"line":212},[83,29141,29142],{"class":307},"  plugins",[83,29144,624],{"class":132},[83,29146,26885],{"class":132},[83,29148,29149,29152],{"class":85,"line":217},[83,29150,29151],{"class":974},"    vue",[83,29153,29154],{"class":132},"(),\n",[83,29156,29157,29160],{"class":85,"line":223},[83,29158,29159],{"class":974},"    vueDevTools",[83,29161,29154],{"class":132},[83,29163,29164,29167,29169],{"class":85,"line":235},[83,29165,29166],{"class":974},"    tailwindcss",[83,29168,3979],{"class":132},[83,29170,29171],{"class":167}," \u002F\u002F Agregamos a la configuración de Vite\n",[83,29173,29174],{"class":85,"line":279},[83,29175,27010],{"class":132},[83,29177,29178,29181,29183],{"class":85,"line":290},[83,29179,29180],{"class":307},"  resolve",[83,29182,624],{"class":132},[83,29184,27195],{"class":132},[83,29186,29187,29190,29192],{"class":85,"line":295},[83,29188,29189],{"class":307},"    alias",[83,29191,624],{"class":132},[83,29193,27195],{"class":132},[83,29195,29196,29199,29202,29204,29206,29208,29210,29213,29215,29217,29219,29222,29224,29226,29228,29230,29232,29234,29237],{"class":85,"line":319},[83,29197,29198],{"class":246},"      '",[83,29200,29201],{"class":250},"@",[83,29203,961],{"class":246},[83,29205,624],{"class":132},[83,29207,29017],{"class":974},[83,29209,187],{"class":132},[83,29211,29212],{"class":512},"new",[83,29214,29022],{"class":974},[83,29216,187],{"class":132},[83,29218,961],{"class":246},[83,29220,29221],{"class":250},".\u002Fsrc",[83,29223,961],{"class":246},[83,29225,256],{"class":132},[83,29227,26990],{"class":89},[83,29229,133],{"class":132},[83,29231,26196],{"class":307},[83,29233,133],{"class":132},[83,29235,29236],{"class":852},"url",[83,29238,29239],{"class":132},")),\n",[83,29241,29242],{"class":85,"line":357},[83,29243,26937],{"class":132},[83,29245,29246],{"class":85,"line":392},[83,29247,27348],{"class":132},[83,29249,29250],{"class":85,"line":421},[83,29251,27015],{"class":132},[12,29253,29254,29255,29258],{},"Luego en el archivo ",[61,29256,29257],{},"src\u002Fassets\u002Fmain.css",", reemplaza todo el contenido por lo siguiente:",[74,29260,29264],{"className":29261,"code":29262,"language":29263,"meta":79,"style":79},"language-css shiki shiki-themes vitesse-light vitesse-dark","@import '.\u002Fbase.css';\n\n@import 'tailwindcss';\n","css",[61,29265,29266,29281,29285],{"__ignoreMap":79},[83,29267,29268,29270,29272,29274,29277,29279],{"class":85,"line":86},[83,29269,29201],{"class":132},[83,29271,90],{"class":89},[83,29273,4009],{"class":246},[83,29275,29276],{"class":250},".\u002Fbase.css",[83,29278,961],{"class":246},[83,29280,25895],{"class":132},[83,29282,29283],{"class":85,"line":103},[83,29284,161],{"emptyLinePlaceholder":160},[83,29286,29287,29289,29291,29293,29296,29298],{"class":85,"line":116},[83,29288,29201],{"class":132},[83,29290,90],{"class":89},[83,29292,4009],{"class":246},[83,29294,29295],{"class":250},"tailwindcss",[83,29297,961],{"class":246},[83,29299,25895],{"class":132},[12,29301,29302,29303,29306],{},"Aprovechamos a limpiar el archivo ",[61,29304,29305],{},"src\u002Fassets\u002Fbase.css"," y dejar solo lo necesario:",[74,29308,29310],{"className":29261,"code":29309,"language":29263,"meta":79,"style":79},"*,\n*::before,\n*::after {\n  box-sizing: border-box;\n  margin: 0;\n  font-weight: normal;\n}\n\nbody {\n  min-height: 100vh;\n  color: #333;\n  background: #fff;\n  transition:\n    color 0.5s,\n    background-color 0.5s;\n  line-height: 1.6;\n  font-family: Inter, sans-serif;\n  font-size: 15px;\n  text-rendering: optimizeLegibility;\n  -webkit-font-smoothing: antialiased;\n  -moz-osx-font-smoothing: grayscale;\n}\n",[61,29311,29312,29318,29330,29341,29353,29364,29376,29380,29384,29390,29405,29420,29434,29442,29455,29466,29478,29495,29509,29521,29533,29545],{"__ignoreMap":79},[83,29313,29314,29316],{"class":85,"line":86},[83,29315,528],{"class":89},[83,29317,4143],{"class":132},[83,29319,29320,29322,29325,29328],{"class":85,"line":103},[83,29321,528],{"class":89},[83,29323,29324],{"class":132},"::",[83,29326,29327],{"class":852},"before",[83,29329,4143],{"class":132},[83,29331,29332,29334,29336,29339],{"class":85,"line":116},[83,29333,528],{"class":89},[83,29335,29324],{"class":132},[83,29337,29338],{"class":852},"after",[83,29340,27195],{"class":132},[83,29342,29343,29346,29348,29351],{"class":85,"line":124},[83,29344,29345],{"class":307},"  box-sizing",[83,29347,624],{"class":132},[83,29349,29350],{"class":1020}," border-box",[83,29352,25895],{"class":132},[83,29354,29355,29358,29360,29362],{"class":85,"line":144},[83,29356,29357],{"class":307},"  margin",[83,29359,624],{"class":132},[83,29361,984],{"class":190},[83,29363,25895],{"class":132},[83,29365,29366,29369,29371,29374],{"class":85,"line":157},[83,29367,29368],{"class":307},"  font-weight",[83,29370,624],{"class":132},[83,29372,29373],{"class":1020}," normal",[83,29375,25895],{"class":132},[83,29377,29378],{"class":85,"line":164},[83,29379,28036],{"class":132},[83,29381,29382],{"class":85,"line":171},[83,29383,161],{"emptyLinePlaceholder":160},[83,29385,29386,29388],{"class":85,"line":197},[83,29387,26311],{"class":89},[83,29389,27195],{"class":132},[83,29391,29392,29395,29397,29400,29403],{"class":85,"line":212},[83,29393,29394],{"class":307},"  min-height",[83,29396,624],{"class":132},[83,29398,29399],{"class":190}," 100",[83,29401,29402],{"class":512},"vh",[83,29404,25895],{"class":132},[83,29406,29407,29410,29412,29415,29418],{"class":85,"line":217},[83,29408,29409],{"class":307},"  color",[83,29411,624],{"class":132},[83,29413,29414],{"class":132}," 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Primero, detén el servidor de desarrollo si está corriendo (",[61,29553,29554],{},"Ctrl + C"," en la terminal) y luego vuelve a iniciarlo:",[74,29557,29558],{"className":24218,"code":24466,"language":24220,"meta":79,"style":79},[61,29559,29560],{"__ignoreMap":79},[83,29561,29562,29564,29566],{"class":85,"line":86},[83,29563,24156],{"class":974},[83,29565,24455],{"class":250},[83,29567,24477],{"class":250},[12,29569,26411,29570,29572],{},[61,29571,26414],{}," y reemplaza todo el contenido por lo siguiente:",[74,29574,29576],{"className":26417,"code":29575,"language":25920,"meta":79,"style":79},"\u003Cscript setup>\nimport { RouterLink, RouterView } from 'vue-router';\n\u003C\u002Fscript>\n\n\u003Ctemplate>\n  \u003Cdiv class=\"flex h-screen flex-col bg-gray-50\">\n    \u003C!-- App Bar -->\n    \u003Cheader class=\"flex h-16 items-center justify-between bg-white px-6 shadow-sm\">\n      \u003Cdiv class=\"text-xl font-bold text-gray-800\">My Project\u003C\u002Fdiv>\n      \u003Cnav class=\"flex gap-4\" aria-label=\"Main Navigation\">\n        \u003Ca href=\"#\" class=\"text-gray-600 hover:text-gray-900\">Home\u003C\u002Fa>\n        \u003Ca href=\"#\" class=\"text-gray-600 hover:text-gray-900\">Profile\u003C\u002Fa>\n      \u003C\u002Fnav>\n    \u003C\u002Fheader>\n\n    \u003Cdiv class=\"flex flex-1 overflow-hidden\">\n      \u003C!-- Sidebar -->\n      \u003Caside class=\"w-64 overflow-y-auto bg-white border-r border-gray-200\">\n        \u003Cnav class=\"p-4 space-y-2\" aria-label=\"Sidebar Navigation\">\n          \u003CRouterLink\n            to=\"\u002F\"\n            class=\"block rounded-md px-4 py-2 text-gray-700 hover:bg-gray-100\"\n            exact-active-class=\"text-indigo-700 font-bold\"\n          >\n            Home\n          \u003C\u002FRouterLink>\n          \u003CRouterLink\n            to=\"\u002Fabout\"\n            class=\"block rounded-md px-4 py-2 text-gray-700 hover:bg-gray-100\"\n            exact-active-class=\"text-indigo-700 font-bold\"\n          >\n            About\n          \u003C\u002FRouterLink>\n        \u003C\u002Fnav>\n      \u003C\u002Faside>\n\n      \u003C!-- Main Content -->\n      \u003Cmain class=\"flex-1 overflow-y-auto p-6\">\n        \u003CRouterView \u002F>\n      \u003C\u002Fmain>\n    \u003C\u002Fdiv>\n\n    \u003C!-- Footer -->\n    \u003Cfooter\n      class=\"flex h-12 items-center justify-center bg-white border-t border-gray-200 text-sm text-gray-500\"\n    >\n      © 2025 My Project. All rights reserved.\n    \u003C\u002Ffooter>\n  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p-6",[83,30074,247],{"class":246},[83,30076,969],{"class":132},[83,30078,30079,30081,30083],{"class":85,"line":708},[83,30080,26635],{"class":132},[83,30082,26724],{"class":89},[83,30084,26211],{"class":132},[83,30086,30087,30089,30091],{"class":85,"line":760},[83,30088,26692],{"class":132},[83,30090,30063],{"class":89},[83,30092,969],{"class":132},[83,30094,30095,30097,30099],{"class":85,"line":765},[83,30096,26701],{"class":132},[83,30098,26320],{"class":89},[83,30100,969],{"class":132},[83,30102,30103],{"class":85,"line":829},[83,30104,161],{"emptyLinePlaceholder":160},[83,30106,30107],{"class":85,"line":863},[83,30108,30109],{"class":167},"    \u003C!-- Footer -->\n",[83,30111,30112,30114],{"class":85,"line":25804},[83,30113,26193],{"class":132},[83,30115,30116],{"class":89},"footer\n",[83,30118,30119,30122,30124,30126,30129],{"class":85,"line":25814},[83,30120,30121],{"class":852},"      class",[83,30123,229],{"class":132},[83,30125,247],{"class":246},[83,30127,30128],{"class":250},"flex h-12 items-center justify-center bg-white border-t border-gray-200 text-sm text-gray-500",[83,30130,29924],{"class":246},[83,30132,30133],{"class":85,"line":25823},[83,30134,30135],{"class":132},"    >\n",[83,30137,30139,30142,30145,30147],{"class":85,"line":30138},47,[83,30140,30141],{"class":132},"      &",[83,30143,30144],{"class":1020},"copy",[83,30146,29115],{"class":132},[83,30148,30149],{"class":93}," 2025 My Project. All rights reserved.\n",[83,30151,30153,30155,30158],{"class":85,"line":30152},48,[83,30154,26701],{"class":132},[83,30156,30157],{"class":89},"footer",[83,30159,969],{"class":132},[83,30161,30163,30165,30167],{"class":85,"line":30162},49,[83,30164,26300],{"class":132},[83,30166,26320],{"class":89},[83,30168,969],{"class":132},[83,30170,30172,30174,30176],{"class":85,"line":30171},50,[83,30173,26291],{"class":132},[83,30175,26495],{"class":89},[83,30177,969],{"class":132},[12,30179,30180,30181,30183],{},"Con esto hemos creado una estructura básica con un app bar, un sidebar, un área principal de contenido y un footer, todo estilizado con clases de Tailwind CSS.\nIdealmente cada bloque (AppBar, Sidebar, Footer) debería ser un componente separado para promover la reutilización y el mantenimiento, pero para este ejemplo lo dejamos todo en ",[61,30182,24901],{}," para simplificar.",[12,30185,30186,30187,30190],{},"Verifica que todo funcione correctamente abriendo ",[61,30188,30189],{},"http:\u002F\u002Flocalhost:5173"," en tu navegador. Deberías ver la estructura básica con estilos aplicados.",[12,30192,30193,30194,30198,30199,133],{},"Con esto ya tienes Tailwind CSS v4 funcionando en tu proyecto. Explora su ",[19,30195,24539],{"href":30196,"target":17502,"rel":30197},"https:\u002F\u002Ftailwindcss.com",[17504,17505]," e instala su extensión para un mejor autocompletado en VS Code: ",[19,30200,30203],{"href":30201,"target":17502,"rel":30202},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=bradlc.vscode-tailwindcss",[17504,17505],"Tailwind CSS IntelliSense",[29,30205],{},[32,30207,30209],{"id":30208},"extra-subiendo-el-proyecto-a-github","EXTRA: Subiendo el proyecto a GitHub",[12,30211,30212],{},"Para esto tenemos muchas opciones. Antes de comenzar asumo que ya tienes una cuenta en GitHub y que tienes Git instalado en tu máquina.",[1406,30214,30215],{},[1362,30216,30217],{},"Primero inicializamos un repositorio Git en la carpeta del proyecto:",[74,30219,30221],{"className":24218,"code":30220,"language":24220,"meta":79,"style":79},"git init\n",[61,30222,30223],{"__ignoreMap":79},[83,30224,30225,30228],{"class":85,"line":86},[83,30226,30227],{"class":974},"git",[83,30229,30230],{"class":250}," init\n",[1406,30232,30233],{"start":103},[1362,30234,30235,30236,30239],{},"Luego creamos un archivo ",[61,30237,30238],{},".gitignore"," en la raíz del proyecto (es probable que ya lo tengas) y nos aseguraremos de tener las siguientes líneas para ignorar archivos y carpetas innecesarias:",[74,30241,30244],{"className":30242,"code":30243,"language":2235},[2816],"# Logs\nlogs\n*.log\nnpm-debug.log*\nyarn-debug.log*\nyarn-error.log*\npnpm-debug.log*\nlerna-debug.log*\n\nnode_modules\n.DS_Store\ndist\ndist-ssr\ncoverage\n*.local\n\n# Editor directories and files\n.vscode\u002F*\n!.vscode\u002Fextensions.json\n.idea\n*.suo\n*.ntvs*\n*.njsproj\n*.sln\n*.sw?\n\n*.tsbuildinfo\n\n.eslintcache\n\n# Cypress\n\u002Fcypress\u002Fvideos\u002F\n\u002Fcypress\u002Fscreenshots\u002F\n\n# Vitest\n__screenshots__\u002F\n\n",[61,30245,30243],{"__ignoreMap":79},[1406,30247,30248],{"start":116},[1362,30249,30250],{},"Ahora agregamos todos los archivos y hacemos el commit inicial:",[74,30252,30254],{"className":24218,"code":30253,"language":24220,"meta":79,"style":79},"git add .\n",[61,30255,30256],{"__ignoreMap":79},[83,30257,30258,30260,30263],{"class":85,"line":86},[83,30259,30227],{"class":974},[83,30261,30262],{"class":250}," add",[83,30264,30265],{"class":250}," .\n",[74,30267,30269],{"className":24218,"code":30268,"language":24220,"meta":79,"style":79},"git commit -m \"Initial commit\"\n",[61,30270,30271],{"__ignoreMap":79},[83,30272,30273,30275,30278,30281,30283,30286],{"class":85,"line":86},[83,30274,30227],{"class":974},[83,30276,30277],{"class":250}," commit",[83,30279,30280],{"class":1020}," -m",[83,30282,259],{"class":246},[83,30284,30285],{"class":250},"Initial commit",[83,30287,29924],{"class":246},[1406,30289,30290,30297],{"start":124},[1362,30291,30292,30293,30296],{},"Ahora vamos a GitHub y creamos un nuevo repositorio. Puedes hacer esto haciendo clic en el botón \"+\" en la esquina superior derecha y seleccionando \"New repository\". Ponle un nombre a tu repositorio (por ejemplo, ",[61,30294,30295],{},"my-vue-app","), agrega una descripción si quieres, y déjalo como público o privado según prefieras. No agregues ningún archivo adicional (como README, .gitignore o licencia), ya los tenemos localmente.",[1362,30298,30299],{},"Luego, seguimos las instrucciones que GitHub nos da para conectar nuestro repositorio local con el remoto. Normalmente son algo así:",[74,30301,30303],{"className":24218,"code":30302,"language":24220,"meta":79,"style":79},"git remote add origin https:\u002F\u002Fexample-url.git\n",[61,30304,30305],{"__ignoreMap":79},[83,30306,30307,30309,30312,30314,30317],{"class":85,"line":86},[83,30308,30227],{"class":974},[83,30310,30311],{"class":250}," remote",[83,30313,30262],{"class":250},[83,30315,30316],{"class":250}," origin",[83,30318,30319],{"class":250}," https:\u002F\u002Fexample-url.git\n",[74,30321,30323],{"className":24218,"code":30322,"language":24220,"meta":79,"style":79},"git branch -M main\n",[61,30324,30325],{"__ignoreMap":79},[83,30326,30327,30329,30332,30335],{"class":85,"line":86},[83,30328,30227],{"class":974},[83,30330,30331],{"class":250}," branch",[83,30333,30334],{"class":1020}," -M",[83,30336,30337],{"class":250}," main\n",[74,30339,30341],{"className":24218,"code":30340,"language":24220,"meta":79,"style":79},"git push -u origin main\n",[61,30342,30343],{"__ignoreMap":79},[83,30344,30345,30347,30350,30353,30355],{"class":85,"line":86},[83,30346,30227],{"class":974},[83,30348,30349],{"class":250}," push",[83,30351,30352],{"class":1020}," -u",[83,30354,30316],{"class":250},[83,30356,30337],{"class":250},[1406,30358,30359],{"start":157},[1362,30360,30361],{},"Verificamos status",[74,30363,30365],{"className":24218,"code":30364,"language":24220,"meta":79,"style":79},"git status\n",[61,30366,30367],{"__ignoreMap":79},[83,30368,30369,30371],{"class":85,"line":86},[83,30370,30227],{"class":974},[83,30372,30373],{"class":250}," status\n",[12,30375,30376,30377,30379,30380,30383],{},"Debe decir que estamos en la rama ",[61,30378,30063],{},", estamos sincronizados con el repositorio remoto ",[61,30381,30382],{},"origin\u002Fmain"," y que no hay nada para hacer commit.",[1406,30385,30386],{"start":164},[1362,30387,30388],{},"Finalmente, cada vez que hagamos cambios y queramos subirlos a GitHub, hacemos:",[74,30390,30392],{"className":24218,"code":30391,"language":24220,"meta":79,"style":79},"git add .\ngit commit -m \"Descripción de los cambios\"\ngit push\n",[61,30393,30394,30402,30417],{"__ignoreMap":79},[83,30395,30396,30398,30400],{"class":85,"line":86},[83,30397,30227],{"class":974},[83,30399,30262],{"class":250},[83,30401,30265],{"class":250},[83,30403,30404,30406,30408,30410,30412,30415],{"class":85,"line":103},[83,30405,30227],{"class":974},[83,30407,30277],{"class":250},[83,30409,30280],{"class":1020},[83,30411,259],{"class":246},[83,30413,30414],{"class":250},"Descripción de los cambios",[83,30416,29924],{"class":246},[83,30418,30419,30421],{"class":85,"line":116},[83,30420,30227],{"class":974},[83,30422,30423],{"class":250}," push\n",[12,30425,30426],{},"¡Y eso es todo! Ahora tienes tu proyecto Vue 3 con Vite subido a GitHub.",[12,30428,30429],{},"Lo normal es que siempre uses un controlador de versiones como Git para manejar tu código, incluso en proyectos personales. Te ayudará a mantener un historial de cambios, colaborar con otros y proteger tu trabajo.",[12,30431,30432,30433,30438],{},"Te recomiendo explorar también sobre ",[19,30434,30437],{"href":30435,"target":17502,"rel":30436},"https:\u002F\u002Fwww.conventionalcommits.org\u002Fen\u002Fv1.0.0\u002F",[17504,17505],"Conventional Commits"," para mantener mensajes de commit consistentes y significativos. Es algo que usan muchas empresas, equipos y proyectos open source.",[12,30440,30441],{},"Algunos recursos para aprender más sobre Git y GitHub:",[1359,30443,30444,30451,30458],{},[1362,30445,30446],{},[19,30447,30450],{"href":30448,"target":17502,"rel":30449},"https:\u002F\u002Fgithub.com\u002Fdjayepro3\u002FGuide-Git-GitHub-VSCode",[17504,17505],"Git & GitHub with VS Code: A Beginner's Guide",[1362,30452,30453],{},[19,30454,30457],{"href":30455,"target":17502,"rel":30456},"https:\u002F\u002Fdocs.github.com\u002Fen\u002Fget-started\u002Fstart-your-journey",[17504,17505],"GitHub Quickstart Guide",[1362,30459,30460],{},[19,30461,30464],{"href":30462,"target":17502,"rel":30463},"https:\u002F\u002Fgit-scm.com\u002Fdoc",[17504,17505],"Git Documentation",[12,30466,30467],{},"Extensiones para VS Code:",[1359,30469,30470,30477],{},[1362,30471,30472],{},[19,30473,30476],{"href":30474,"target":17502,"rel":30475},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=eamodio.gitlens",[17504,17505],"Gitlens",[1362,30478,30479],{},[19,30480,30483],{"href":30481,"target":17502,"rel":30482},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=mhutchie.git-graph",[17504,17505],"Git Graph",[29,30485],{},[32,30487,30489],{"id":30488},"extra-otras-extensiones-útiles-para-vs-code","EXTRA: Otras extensiones útiles para VS Code",[12,30491,30492],{},"Algunas extensiones que siempre recomiendo para VS Code (sin importar el tipo de proyecto):",[1359,30494,30495,30503,30511,30519],{},[1362,30496,30497,30502],{},[19,30498,30501],{"href":30499,"target":17502,"rel":30500},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=usernamehw.errorlens",[17504,17505],"Error Lens",": Resalta errores y advertencias directamente en el código, facilitando su identificación y corrección.",[1362,30504,30505,30510],{},[19,30506,30509],{"href":30507,"target":17502,"rel":30508},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=naumovs.color-highlight",[17504,17505],"Color Highlight",": Resalta los colores definidos en tu código CSS, facilitando la visualización de los mismos.",[1362,30512,30513,30518],{},[19,30514,30517],{"href":30515,"target":17502,"rel":30516},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=aaron-bond.better-comments",[17504,17505],"Better Comments",": Mejora la legibilidad de los comentarios en el código mediante colores y estilos.",[1362,30520,30521,30526,30527,30532],{},[19,30522,30525],{"href":30523,"target":17502,"rel":30524},"https:\u002F\u002Fmarketplace.visualstudio.com\u002Fitems?itemName=antfu.iconify",[17504,17505],"Iconify Intellisense",": Si quieres trabajar con iconos, esta extensión te permite buscar e insertar iconos de múltiples bibliotecas directamente en tu código. A parte de ello recomiendo explorar su librería ",[19,30528,30531],{"href":30529,"target":17502,"rel":30530},"https:\u002F\u002Ficon-sets.iconify.design\u002F",[17504,17505],"Iconify"," dónde puedes encontrar una gran variedad de icon sets gratuitos.",[29,30534],{},[12,30536,30537],{},"Bueno, eso sería todo para esta guía introductoria sobre Vue 3 con Vite. Espero que te haya sido útil para comenzar tu viaje con este framework y su ecosistema.",[29,30539],{},[4374,30541,30542],{},"html pre.shiki code .s_xSY, html code.shiki .s_xSY{--shiki-default:#59873A;--shiki-dark:#80A665}html pre.shiki code .spP0B, html code.shiki .spP0B{--shiki-default:#B56959;--shiki-dark:#C98A7D}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html pre.shiki code .sHLBJ, html code.shiki .sHLBJ{--shiki-default:#998418;--shiki-dark:#B8A965}html pre.shiki code .snYqZ, html code.shiki .snYqZ{--shiki-default:#A0ADA0;--shiki-dark:#758575DD}html pre.shiki code .sTPum, html code.shiki .sTPum{--shiki-default:#1E754F;--shiki-dark:#4D9375}html pre.shiki code .scnC2, html code.shiki .scnC2{--shiki-default:#B5695977;--shiki-dark:#C98A7D77}html pre.shiki code .si6no, html code.shiki .si6no{--shiki-default:#999999;--shiki-dark:#666666}html pre.shiki code .s9nN2, html code.shiki .s9nN2{--shiki-default:#B07D48;--shiki-dark:#BD976A}html pre.shiki code .s5TCs, html code.shiki .s5TCs{--shiki-default:#AB5959;--shiki-dark:#CB7676}html pre.shiki code .s8w-G, html code.shiki .s8w-G{--shiki-default:#393A34;--shiki-dark:#DBD7CAEE}html pre.shiki code .sfsYZ, html code.shiki .sfsYZ{--shiki-default:#A65E2B;--shiki-dark:#C99076}html pre.shiki code .sqbOQ, html code.shiki .sqbOQ{--shiki-default:#2F798A;--shiki-dark:#4C9A91}",{"title":79,"searchDepth":116,"depth":116,"links":30544},[30545,30546,30547,30548,30552,30553,30554,30559,30560,30561,30562],{"id":24131,"depth":103,"text":24132},{"id":24191,"depth":103,"text":24192},{"id":24211,"depth":103,"text":24212},{"id":24545,"depth":103,"text":24546,"children":30549},[30550,30551],{"id":24829,"depth":116,"text":24830},{"id":24911,"depth":116,"text":24912},{"id":25864,"depth":103,"text":25865},{"id":27128,"depth":103,"text":27129},{"id":27760,"depth":103,"text":27761,"children":30555},[30556,30557,30558],{"id":28640,"depth":116,"text":28641},{"id":28673,"depth":116,"text":28674},{"id":28754,"depth":116,"text":28755},{"id":28811,"depth":103,"text":28812},{"id":28957,"depth":103,"text":28958},{"id":30208,"depth":103,"text":30209},{"id":30488,"depth":103,"text":30489},"2025-12-04","\u002Fblog\u002Fgetting-started-vue-vite\u002Fshared\u002Fvite+vue.webp","2025-12-22",{},"\u002Fblog\u002Fblog\u002Fgetting-started-vue-vite",{"title":24119,"description":24124},{"loc":30570,"priority":4394,"lastmod":30565},"\u002Fes\u002Fblog\u002Fgetting-started-vue-vite","getting-started-vue-vite","blog\u002Fblog\u002Fgetting-started-vue-vite","Una guía completa para configurar tu primer proyecto Vue 3 con Vite, incluyendo mejores prácticas y herramientas modernas.",[30575,30576,30577],"Vue.js","Vite","Tailwind CSS","Bf_UMGO80INaHK2ReFgXeiuNNUWLLa8TjxgIErcTvgI",1776805792119]