Feature selection for bankruptcy prediction: a multi-objective optimization approach

In this work a Multi-Objective Evolutionary Algorithm (MOEA) was applied for feature selection in the problem of bankruptcy prediction. The aim is to maximize the accuracy of the classifier while keeping the number of features low. A two-objective problem - minimization of the number of features and...

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Detalhes bibliográficos
Autor principal: Gaspar-Cunha, A. (author)
Outros Autores: Mendes, F. (author), Duarte, J. (author), Vieira, Armando (author), Ribeiro, Bernardete (author), Ribeiro, André M. S. (author), Neves, João Carvalho (author)
Formato: bookPart
Idioma:eng
Publicado em: 2012
Assuntos:
Feature selection
Bankruptcy prediction
Multi-objective optimization
Evolutionary algorithms
Support vector machines
Logistic regression
Texto completo:http://hdl.handle.net/1822/13218
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/13218

Texto Completo

http://hdl.handle.net/1822/13218

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