{"id":14968,"date":"2018-03-09T09:01:55","date_gmt":"2018-03-09T09:01:55","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/aplicacion-del-principio-inductivo-de-mevr-en-la-construccion-de-clasificadores\/"},"modified":"2018-03-09T09:01:55","modified_gmt":"2018-03-09T09:01:55","slug":"aplicacion-del-principio-inductivo-de-mevr-en-la-construccion-de-clasificadores","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/aplicacion-del-principio-inductivo-de-mevr-en-la-construccion-de-clasificadores\/","title":{"rendered":"Aplicaci\u00f3n del principio inductivo de mevr en la construcci\u00f3n de clasificadores"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Mar\u00eda  Mar Abad Grau <\/strong><\/h2>\n<p>El objetivo general de esta tesis ha sido el estudio y obtenci\u00f3n de calsificadores con niveles aceptables de eficiencia y exactitud mediante la utilizaci\u00f3n de alg\u00fan nuevo principio inductivo de manera que sean capaces de tratar con grandes vol\u00famenes de datos de forma eficiente, sean tolerantes a atributos ruidosos o inconsistentes y capaces de trabajar con atributos discretos y continuos.  para ello se han utilizado dos principios avanzados: el principio inductivo de minimizaci\u00f3n estructural vectorial del riesgo mevr y el enfoque bayesiano. el principio de mevr se ha aplicado a diferentes tareas:  a,- a la definici\u00f3n de un nuevo algoritmo de discretizaci\u00f3n, llamado discretizaci\u00f3n estructural, que ser\u00e1 usado por los algoritmos de aprendizaje que requieran de una previa discretizaci\u00f3n de las variables continuas.  b,- a la definici\u00f3n de un algoritmo de clasificaci\u00f3n basado en redes bayesianas. En concreto se aplica en la construcci\u00f3n de la estructura del clasificador. Se trata del algoritmo que hemos llamado simple generalizado estructurado sge.  c,- a la definici\u00f3n de dos algortimos de selecci\u00f3n de atributos aplicables especialmente a clasificadores poco tolerantes a atributos sup\u00e9rfluos, como los basados en instancias.  en concreto se trata de un algoritmo de selecci\u00f3n hacia delante, el algoritmo de inclusi\u00f3n acotada (ia) y otros de selecci\u00f3n  hacia atr\u00e1s: el algoritmo de poda acotada. Asimismo se aplica la estad\u00edstica bayesiana como alternativa a la cl\u00e1sica para:  a,- mejorar los resultados obtenidos con el algoritmo sge, memdiante el uso de un factor bayesiano de suavizado para la definici\u00f3n de los par\u00e1metros de la red, obteni\u00e9ndose el llamado algoritmo simple generalizado estructurado suavizado (sges).  b,- definir un nuevo algoritmo basado en instancias llamado bayesiano transductivo (bt).  la aplicaci\u00f3n del algoritmo de ia a la selecci\u00f3n de atributos junto con este algoritmo nos lleva a definir el<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Aplicaci\u00f3n del principio inductivo de mevr en la construcci\u00f3n de clasificadores<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Aplicaci\u00f3n del principio inductivo de mevr en la construcci\u00f3n de clasificadores <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Mar\u00eda  Mar Abad Grau <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Murcia<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 21\/12\/2001<\/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> Hern\u00e1ndez Molinero Luis Daniel<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: fernando Martin rubio <\/li>\n<li>seraf\u00edn Moral callej\u00f3n (vocal)<\/li>\n<li>Juan  Carlos Torres cantero (vocal)<\/li>\n<li>Antonio Salmer\u00f3n cerd\u00e1n (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Mar\u00eda Mar Abad Grau El objetivo general de esta tesis ha sido el estudio y obtenci\u00f3n de [&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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