{"id":53405,"date":"2018-03-09T22:41:04","date_gmt":"2018-03-09T22:41:04","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/tecnicas-de-submuestreo-toma-de-decisiones-y-analisis-de-diversidad-en-aprendizaje-supervisado-con-sistemas-multiples-de-clasificacion\/"},"modified":"2018-03-09T22:41:04","modified_gmt":"2018-03-09T22:41:04","slug":"tecnicas-de-submuestreo-toma-de-decisiones-y-analisis-de-diversidad-en-aprendizaje-supervisado-con-sistemas-multiples-de-clasificacion","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/tecnicas-de-submuestreo-toma-de-decisiones-y-analisis-de-diversidad-en-aprendizaje-supervisado-con-sistemas-multiples-de-clasificacion\/","title":{"rendered":"Tecnicas de submuestreo, toma de decisiones y analisis de diversidad en aprendizaje supervisado con sistemas multiples de clasificacion"},"content":{"rendered":"<h2>Tesis doctoral de <strong>  Valdovinos Rosas Rosa Mar\u00eda <\/strong><\/h2>\n<p>En la presente tesis doctoral, se analiza fundamentalmente la aplicabilidad de los sistemas de m\u00faltiple clasificaci\u00f3n (smc) en el marco de la regla del vecino m\u00e1s cercano. Una primera l\u00ednea fundamental de investigaci\u00f3n se centra en los algoritmos de preprocesado, con el objetivo de resolver diferentes problemas relacionados con la calidad de la muestra de entrenamiento: presencia de patrones redundantes, at\u00edpicos o ruidosos, bases de datos con un tama\u00f1o excesivo y desbalance entre las distribuciones de las clases. otro aspecto de gran relevancia hace referencia a la efectividad de los componentes individuales del smc dentro del m\u00e9todo de votaci\u00f3n, para lo cual se proponen nuevas t\u00e9cnicas de ponderaci\u00f3n din\u00e1mica y est\u00e1tica de las decisiones individuales. El tercer punto central se refiere al an\u00e1lisis de diversidad de los clasificadores, utilizando para ello diversas medidas existentes en la literatura af\u00edn. Otras cuestiones ampliamente analizadas a lo largo de esta tesis son: las t\u00e9cnicas de muestreo (bagging, boosting, arcing y selecci\u00f3n secuencial aleatoria), el tama\u00f1o del smc y, por \u00faltimo, la viabilidad de utilizar dos modelos de redes neuronales artificiales (perceptr\u00f3n multicapa y red modular).<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Tecnicas de submuestreo, toma de decisiones y analisis de diversidad en aprendizaje supervisado con sistemas multiples de clasificacion<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Tecnicas de submuestreo, toma de decisiones y analisis de diversidad en aprendizaje supervisado con sistemas multiples de clasificacion <\/li>\n<li><strong>Autor:<\/strong>\u00a0  Valdovinos Rosas Rosa Mar\u00eda <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Jaume i de castell\u00f3n<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 23\/06\/2006<\/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> Sanchez Garreta Jos\u00e9 Salvador<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: filiberto Pla ba\u00f1on <\/li>\n<li>jordi Vitri? marca (vocal)<\/li>\n<li> Mico Andr\u00e9s Mar\u00eda  Luisa (vocal)<\/li>\n<li>Jos\u00e9 crist\u00f3bal Riquelme santos (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Valdovinos Rosas Rosa Mar\u00eda En la presente tesis doctoral, se analiza fundamentalmente la aplicabilidad de los sistemas [&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 center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","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-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-gradient":""}},"ast-content-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-gradient":""},"tablet":{"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-gradient":""},"mobile":{"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-gradient":""}},"footnotes":""},"categories":[2207,54687,1890,1477,2528,6264,18725,126,30277],"tags":[11903,30472,62593,82760,73320,117858],"class_list":["post-53405","post","type-post","status-publish","format-standard","hentry","category-analisis-de-datos","category-cibernetica","category-ciencia-de-los-ordenadores","category-estadistica","category-inteligencia-artificial","category-investigacion-operativa","category-jaume-i-de-castellon","category-matematicas","category-sistemas-automatizados-de-control-de-calidad","tag-filiberto-pla-banon","tag-jordi-vitri-marca","tag-jose-cristobal-riquelme-santos","tag-mico-andres-maria-luisa","tag-sanchez-garreta-jose-salvador","tag-valdovinos-rosas-rosa-maria"],"_links":{"self":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts\/53405","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/comments?post=53405"}],"version-history":[{"count":0,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts\/53405\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/media?parent=53405"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/categories?post=53405"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/tags?post=53405"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}