Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning

Detalhes bibliográficos
Autor(a) principal: Silvestre, Miriam Rodrigues [UNESP]
Data de Publicação: 2002
Outros Autores: Ling, Lee Luan
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ICPR.2002.1047927
http://hdl.handle.net/11449/67053
Resumo: In this article we describe a feature extraction algorithm for pattern classification based on Bayesian Decision Boundaries and Pruning techniques. The proposed method is capable of optimizing MLP neural classifiers by retaining those neurons in the hidden layer that realy contribute to correct classification. Also in this article we proposed a method which defines a plausible number of neurons in the hidden layer based on the stem-and-leaf graphics of training samples. Experimental investigation reveals the efficiency of the proposed method. © 2002 IEEE.
id UNSP_555639ace940fd88563d00483ba9d322
oai_identifier_str oai:repositorio.unesp.br:11449/67053
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruningBayesian decision boundariesNeuronsPruning techniquesAlgorithmsDecision theoryMathematical modelsNeural networksPattern recognitionIn this article we describe a feature extraction algorithm for pattern classification based on Bayesian Decision Boundaries and Pruning techniques. The proposed method is capable of optimizing MLP neural classifiers by retaining those neurons in the hidden layer that realy contribute to correct classification. Also in this article we proposed a method which defines a plausible number of neurons in the hidden layer based on the stem-and-leaf graphics of training samples. Experimental investigation reveals the efficiency of the proposed method. © 2002 IEEE.Dep. Matematica-FCT-UNESPDECOM-FEEC-UNICAMPDep. Matematica-FCT-UNESPUniversidade Estadual Paulista (Unesp)Universidade Estadual de Campinas (UNICAMP)Silvestre, Miriam Rodrigues [UNESP]Ling, Lee Luan2014-05-27T11:20:32Z2014-05-27T11:20:32Z2002-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject387-390http://dx.doi.org/10.1109/ICPR.2002.1047927Proceedings - International Conference on Pattern Recognition, v. 16, n. 3, p. 387-390, 2002.1051-4651http://hdl.handle.net/11449/6705310.1109/ICPR.2002.1047927WOS:0001778871000942-s2.0-337515753033356686459975471Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings - International Conference on Pattern Recognition0,307info:eu-repo/semantics/openAccess2024-06-19T14:32:27Zoai:repositorio.unesp.br:11449/67053Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:55:35.526782Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning
title Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning
spellingShingle Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning
Silvestre, Miriam Rodrigues [UNESP]
Bayesian decision boundaries
Neurons
Pruning techniques
Algorithms
Decision theory
Mathematical models
Neural networks
Pattern recognition
title_short Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning
title_full Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning
title_fullStr Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning
title_full_unstemmed Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning
title_sort Optimization of neural classifiers based on bayesian decision boundaries and idle neurons pruning
author Silvestre, Miriam Rodrigues [UNESP]
author_facet Silvestre, Miriam Rodrigues [UNESP]
Ling, Lee Luan
author_role author
author2 Ling, Lee Luan
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade Estadual de Campinas (UNICAMP)
dc.contributor.author.fl_str_mv Silvestre, Miriam Rodrigues [UNESP]
Ling, Lee Luan
dc.subject.por.fl_str_mv Bayesian decision boundaries
Neurons
Pruning techniques
Algorithms
Decision theory
Mathematical models
Neural networks
Pattern recognition
topic Bayesian decision boundaries
Neurons
Pruning techniques
Algorithms
Decision theory
Mathematical models
Neural networks
Pattern recognition
description In this article we describe a feature extraction algorithm for pattern classification based on Bayesian Decision Boundaries and Pruning techniques. The proposed method is capable of optimizing MLP neural classifiers by retaining those neurons in the hidden layer that realy contribute to correct classification. Also in this article we proposed a method which defines a plausible number of neurons in the hidden layer based on the stem-and-leaf graphics of training samples. Experimental investigation reveals the efficiency of the proposed method. © 2002 IEEE.
publishDate 2002
dc.date.none.fl_str_mv 2002-12-01
2014-05-27T11:20:32Z
2014-05-27T11:20:32Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/ICPR.2002.1047927
Proceedings - International Conference on Pattern Recognition, v. 16, n. 3, p. 387-390, 2002.
1051-4651
http://hdl.handle.net/11449/67053
10.1109/ICPR.2002.1047927
WOS:000177887100094
2-s2.0-33751575303
3356686459975471
url http://dx.doi.org/10.1109/ICPR.2002.1047927
http://hdl.handle.net/11449/67053
identifier_str_mv Proceedings - International Conference on Pattern Recognition, v. 16, n. 3, p. 387-390, 2002.
1051-4651
10.1109/ICPR.2002.1047927
WOS:000177887100094
2-s2.0-33751575303
3356686459975471
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings - International Conference on Pattern Recognition
0,307
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 387-390
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808129374250074112

Registros relacionados