Learning and validation in neural network ensembles

Ensembles of artificial neural networks (ANN) have been used in the last years as classification/regression machines, showing improved generalization capabilities that outperform those of single networks. We propose here a simple method for learning and validation in regression/classification ensemb...

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Detalles Bibliográficos
Autores principales: Granitto, Pablo Miguel, Verdes, Pablo Fabián, Ceccatto, Hermenegildo Alejandro, Navone, P. F.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2001
Materias:
Ciencias Informáticas
Learning and validation
ARTIFICIAL INTELLIGENCE
neural network ensembles
Learning
Validation
Neural nets
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/21665
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-21665
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Learning and validation
ARTIFICIAL INTELLIGENCE
neural network ensembles
Learning
Validation
Neural nets
spellingShingle Ciencias Informáticas
Learning and validation
ARTIFICIAL INTELLIGENCE
neural network ensembles
Learning
Validation
Neural nets
Granitto, Pablo Miguel
Verdes, Pablo Fabián
Ceccatto, Hermenegildo Alejandro
Navone, P. F.
Learning and validation in neural network ensembles
topic_facet Ciencias Informáticas
Learning and validation
ARTIFICIAL INTELLIGENCE
neural network ensembles
Learning
Validation
Neural nets
description Ensembles of artificial neural networks (ANN) have been used in the last years as classification/regression machines, showing improved generalization capabilities that outperform those of single networks. We propose here a simple method for learning and validation in regression/classification ensembles of ANN that leads to overtrained aggregate members with an adequate balance between accuracy and diversity. The algorithm is favorably tested against other methods recently proposed in the literature, producing an improvement in performance on the standard statistical databases used as benchmarks.
format Objeto de conferencia
Objeto de conferencia
author Granitto, Pablo Miguel
Verdes, Pablo Fabián
Ceccatto, Hermenegildo Alejandro
Navone, P. F.
author_facet Granitto, Pablo Miguel
Verdes, Pablo Fabián
Ceccatto, Hermenegildo Alejandro
Navone, P. F.
author_sort Granitto, Pablo Miguel
title Learning and validation in neural network ensembles
title_short Learning and validation in neural network ensembles
title_full Learning and validation in neural network ensembles
title_fullStr Learning and validation in neural network ensembles
title_full_unstemmed Learning and validation in neural network ensembles
title_sort learning and validation in neural network ensembles
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/21665
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AT verdespablofabian learningandvalidationinneuralnetworkensembles
AT ceccattohermenegildoalejandro learningandvalidationinneuralnetworkensembles
AT navonepf learningandvalidationinneuralnetworkensembles
bdutipo_str Repositorios
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