{"id":5661,"date":"1995-01-01T00:00:00","date_gmt":"1995-01-01T00:00:00","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/1995\/01\/01\/aprendizaje-de-redes-de-creencia-mediante-la-deteccion-de-independencias-modelos-no-probabilisticos\/"},"modified":"1995-01-01T00:00:00","modified_gmt":"1995-01-01T00:00:00","slug":"aprendizaje-de-redes-de-creencia-mediante-la-deteccion-de-independencias-modelos-no-probabilisticos","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/aprendizaje-de-redes-de-creencia-mediante-la-deteccion-de-independencias-modelos-no-probabilisticos\/","title":{"rendered":"Aprendizaje de redes de creencia mediante la deteccion de independencias: modelos no probabilisticos."},"content":{"rendered":"<h2>Tesis doctoral de <strong> Juan  Francisco Huete Guadix <\/strong><\/h2>\n<p>En la primera parte, la memoria aborda el problema del aprendizaje de varios tipos de redes de creencia (poliarboles y redes simples) a partir, por ejemplo, de bases de datos o de un experto del dominio. La segunda parte de la memoria fija su atencion en dos modelos de incertidumbre particulares, el posibilistico y el de los intervalos de probabilidad, ambos modelos de gran interes. En el primero se hace un estudio a fondo y detallado del concepto de independencia condicional. Se proponen, ademas de la estandar varias definiciones alternativas, muy intuitivas y de buen comportamiento de acuerdo a la axiomatica comunmente aceptada para los modelos de independicia condicional. Se presentan tambien varios metodos para estimar distribuciones de posibilidad. Finalmente, por lo que se refiere al segundo modelo, un formalismo menos estudiado en la literatura, la memoria no se centra exclusivamente en la nocion de independencia, sino que se hace una contribucion significativa en distintos ambitos del mismo, como pueden ser el del condicionamiento el de la estimacion, etc.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Aprendizaje de redes de creencia mediante la deteccion de independencias: modelos no probabilisticos.<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Aprendizaje de redes de creencia mediante la deteccion de independencias: modelos no probabilisticos. <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Juan  Francisco Huete Guadix <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Granada<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 01\/01\/1995<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Luis Miguel De Campos Iba\u00f1ez<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: Miguel Delgado Calvo-flores <\/li>\n<li>Mar\u00eda \u00e1ngeles Gil \u00e1lvarez (vocal)<\/li>\n<li> Godo I Lacas Luis (vocal)<\/li>\n<li>Yosu Yurramendi Mendizabal (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Juan Francisco Huete Guadix En la primera parte, la memoria aborda el problema del aprendizaje de varios [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","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":"","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-4)","background-image":"","background-repeat":"repeat","background-position":"center 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