{"id":3324,"date":"2025-10-06T16:10:26","date_gmt":"2025-10-06T14:10:26","guid":{"rendered":"https:\/\/tecnologia.euroinnova.com\/ajuste-de-modelos-predictivos-en-ia-con-la-funcion-de-verosimilitud\/"},"modified":"2025-10-07T14:50:46","modified_gmt":"2025-10-07T12:50:46","slug":"funcion-verosimilitud","status":"publish","type":"post","link":"https:\/\/tecnologia.euroinnova.com\/en\/funcion-verosimilitud","title":{"rendered":"Fitting predictive models in AI with the likelihood function"},"content":{"rendered":"<article>\n<p>The <strong>funci\u00f3n de verosimilitud<\/strong> es un concepto muy utilizado y fundamental en la estad\u00edstica y el aprendizaje autom\u00e1tico, ya que permite estimar los par\u00e1metros de un modelo a partir de los datos observados.<\/p>\n<p>In the context of the <strong>artificial intelligence (AI)<\/strong>, su aplicaci\u00f3n es necesaria para lograr el ajuste de modelos predictivos, la inferencia bayesiana y la selecci\u00f3n de hip\u00f3tesis en problemas de clasificaci\u00f3n y regresi\u00f3n.<\/p>\n<h2 id=\"que-es-la-funcion-de-verosimilitud-y-como-se-aplica-en-la-ia\">Qu\u00e9 es la <strong>funci\u00f3n de verosimilitud<\/strong> y c\u00f3mo se aplica en la IA<\/h2>\n<p>La funci\u00f3n de verosimilitud cuantifica la <strong>probabilidad de observar un conjunto de datos dado un conjunto de par\u00e1metros del modelo<\/strong>.<\/p>\n<p>Matem\u00e1ticamente, si un conjunto de datos <code>X = { x<sub>1<\/sub>, x<sub>2<\/sub>, \u2026, x<sub>n<\/sub> }<\/code> sigue una distribuci\u00f3n de probabilidad con par\u00e1metros <strong>\u03b8<\/strong>, la funci\u00f3n de verosimilitud se define como:<\/p>\n<p style=\"text-align: center;\"><img decoding=\"async\" src=\"\/wp-content\/uploads\/inline-images\/Funci%C3%B3n%20de%20verosimilitud.jpg\" alt=\"funci\u00f3n de verosimilitud\" width=\"170\" height=\"50\" \/><\/p>\n<p>En la IA y el aprendizaje autom\u00e1tico, esta funci\u00f3n se utiliza para encontrar los <strong>estimadores de m\u00e1xima verosimilitud (MLE, Maximum Likelihood Estimation)<\/strong>, que optimizan los par\u00e1metros para maximizar la probabilidad de los datos observados.<\/p>\n<h3 id=\"ejemplos-practicos-en-aprendizaje-automatico\">Ejemplos pr\u00e1cticos en aprendizaje autom\u00e1tico<\/h3>\n<p>En aprendizaje autom\u00e1tico, la funci\u00f3n de verosimilitud se utiliza para la <strong>estimaci\u00f3n de par\u00e1metros en diversos modelos<\/strong>. Algunos ejemplos podr\u00edan ser:<\/p>\n<ul>\n<li><strong>Regresi\u00f3n log\u00edstica<\/strong>: se emplea la verosimilitud para ajustar los coeficientes del modelo optimizando la funci\u00f3n log-verosimilitud.<\/li>\n<!-- A\u00f1ade m\u00e1s \u00edtems seg\u00fan necesites --><\/ul>\n<\/article>\n\n\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>La funci\u00f3n de verosimilitud es un concepto muy utilizado y fundamental en la estad\u00edstica y el aprendizaje autom\u00e1tico, ya que [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":1001,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3324","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sin-categorizar"],"acf":[],"_links":{"self":[{"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/posts\/3324","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/comments?post=3324"}],"version-history":[{"count":0,"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/posts\/3324\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/media\/1001"}],"wp:attachment":[{"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/media?parent=3324"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/categories?post=3324"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tecnologia.euroinnova.com\/en\/wp-json\/wp\/v2\/tags?post=3324"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}