{"id":86437,"date":"2018-03-10T00:11:03","date_gmt":"2018-03-10T00:11:03","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/safe-sistema-de-aprendizaje-de-funcioens-a-partir-de-ejemplos\/"},"modified":"2018-03-10T00:11:03","modified_gmt":"2018-03-10T00:11:03","slug":"safe-sistema-de-aprendizaje-de-funcioens-a-partir-de-ejemplos","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/safe-sistema-de-aprendizaje-de-funcioens-a-partir-de-ejemplos\/","title":{"rendered":"Safe: sistema de aprendizaje de funcioens a partir de ejemplos"},"content":{"rendered":"<h2>Tesis doctoral de <strong>  Quevedo P\u00e9rez Jos\u00e9 Ram\u00f3n <\/strong><\/h2>\n<p>Hay dos corrientes fundamentales en el aprendizaje autom\u00e1tico a partir de ejemplos: los sitemas que tratan de sintetizar reglas ( u otros mecanismo equivalentes) capaces de clasificar casos no vistos en un conjunto finito de categor\u00edas discretas, y los algoritmos que persiguen la inducci\u00f3n de funicones.  en esta tesis se combinan los dos plantemaientos para obtener un nuevo m\u00e9todo capaz de aprender funciones y que usa, como una herramienta central, unsistema de aprendizaje autom\u00e1tico de categor\u00edas discretas. El resutlado es un mecanimos capaza de manejar de manera natural tanto atributos con valores discretos como continuos y conluyendo funciones parcialmente definidas por aplicaciones lineales a partir de un subconjunto de atributos num\u00e9ricos del dominio.  el sistema as\u00ed obtenido se llama safe, un acr\u00f3nimo de sistema de aprendizaje de funciones a partir de ejemplos, es comparado con \u00e9xito con algoritmos de reconocido prestigio dise\u00f1ados para llevar a cabo esta tarea.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Safe: sistema de aprendizaje de funcioens a partir de ejemplos<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Safe: sistema de aprendizaje de funcioens a partir de ejemplos <\/li>\n<li><strong>Autor:<\/strong>\u00a0  Quevedo P\u00e9rez Jos\u00e9 Ram\u00f3n <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Oviedo<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 19\/09\/2000<\/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>Antonio Bahamonde Rionda<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: jos\u00e9 Mira mira <\/li>\n<li>sen\u00e9n Barro ameneiro (vocal)<\/li>\n<li>ram\u00f3n Rizo aldeguer (vocal)<\/li>\n<li> L\u00f3pez Garc\u00eda Jos\u00e9 secundino (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Quevedo P\u00e9rez Jos\u00e9 Ram\u00f3n Hay dos corrientes fundamentales en el aprendizaje autom\u00e1tico a partir de ejemplos: los [&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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