GA-KDE-Bayes: An evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems

Maria Fernanda Wanderley, Vincent Gardeux, René Natowicz, Antônio P. Braga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Citations (Scopus)

Abstract

This paper presents an evolutionary wrapper method for feature selection that uses a non-parametric density estimation method and a Bayesian Classifier. Non-parametric methods are a good alternative for scarce and sparse data, as in Bioinformatics problems, since they do not make any assumptions about its structure and all the information come from data itself. Results show that local modeling provides small and relevant subsets of features when comparing to results available on literature.

Original languageEnglish (US)
Title of host publicationESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Pages155-160
Number of pages6
StatePublished - 2013
Externally publishedYes
Event21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013 - Bruges, Belgium
Duration: Apr 24 2013Apr 26 2013

Other

Other21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013
CountryBelgium
CityBruges
Period4/24/134/26/13

Fingerprint

Bioinformatics
Feature extraction
Classifiers

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Wanderley, M. F., Gardeux, V., Natowicz, R., & Braga, A. P. (2013). GA-KDE-Bayes: An evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems. In ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 155-160)

GA-KDE-Bayes : An evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems. / Wanderley, Maria Fernanda; Gardeux, Vincent; Natowicz, René; Braga, Antônio P.

ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2013. p. 155-160.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wanderley, MF, Gardeux, V, Natowicz, R & Braga, AP 2013, GA-KDE-Bayes: An evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems. in ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. pp. 155-160, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013, Bruges, Belgium, 4/24/13.
Wanderley MF, Gardeux V, Natowicz R, Braga AP. GA-KDE-Bayes: An evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems. In ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2013. p. 155-160
Wanderley, Maria Fernanda ; Gardeux, Vincent ; Natowicz, René ; Braga, Antônio P. / GA-KDE-Bayes : An evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems. ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2013. pp. 155-160
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