Prediction in health domain using Bayesian networks optimization based on induction learning techniques

"A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and exible methods of reasoning. Obtaining it from data is a learning process that is divided in...

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Autores principales: Felgaer, Pablo, Britos, Paola Verónica, García Martínez, Ramón
Formato: Ponencias en Congresos acceptedVersion
Lenguaje:Inglés
Publicado: 2019
Materias:
TEORIA BAYESIANA DE DECISIONES ESTADISTICAS
APRENDIZAJE
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/1432
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-1432
record_format dspace
spelling I32-R138-123456789-14322022-12-07T14:14:03Z Prediction in health domain using Bayesian networks optimization based on induction learning techniques Felgaer, Pablo Britos, Paola Verónica García Martínez, Ramón TEORIA BAYESIANA DE DECISIONES ESTADISTICAS APRENDIZAJE "A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and exible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain." 2019-01-24T15:58:01Z 2019-01-24T15:58:01Z 2006 Ponencias en Congresos info:eu-repo/semantics/acceptedVersion 0129-1831 http://ri.itba.edu.ar/handle/123456789/1432 en info:eu-repo/semantics/altIdentifier/doi/10.1142/S0129183106008558 application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic TEORIA BAYESIANA DE DECISIONES ESTADISTICAS
APRENDIZAJE
spellingShingle TEORIA BAYESIANA DE DECISIONES ESTADISTICAS
APRENDIZAJE
Felgaer, Pablo
Britos, Paola Verónica
García Martínez, Ramón
Prediction in health domain using Bayesian networks optimization based on induction learning techniques
topic_facet TEORIA BAYESIANA DE DECISIONES ESTADISTICAS
APRENDIZAJE
description "A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and exible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain."
format Ponencias en Congresos
acceptedVersion
author Felgaer, Pablo
Britos, Paola Verónica
García Martínez, Ramón
author_facet Felgaer, Pablo
Britos, Paola Verónica
García Martínez, Ramón
author_sort Felgaer, Pablo
title Prediction in health domain using Bayesian networks optimization based on induction learning techniques
title_short Prediction in health domain using Bayesian networks optimization based on induction learning techniques
title_full Prediction in health domain using Bayesian networks optimization based on induction learning techniques
title_fullStr Prediction in health domain using Bayesian networks optimization based on induction learning techniques
title_full_unstemmed Prediction in health domain using Bayesian networks optimization based on induction learning techniques
title_sort prediction in health domain using bayesian networks optimization based on induction learning techniques
publishDate 2019
url http://ri.itba.edu.ar/handle/123456789/1432
work_keys_str_mv AT felgaerpablo predictioninhealthdomainusingbayesiannetworksoptimizationbasedoninductionlearningtechniques
AT britospaolaveronica predictioninhealthdomainusingbayesiannetworksoptimizationbasedoninductionlearningtechniques
AT garciamartinezramon predictioninhealthdomainusingbayesiannetworksoptimizationbasedoninductionlearningtechniques
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