Geração Automática de Conjuntos de Classificadores Através da Seleção de Características não Supervisionada (Generating Ensemble of Classifiers through Unsupervised Feature Selection)

Marisa Morita (marisa.e.morita@hsbc.com.br)1, Luiz S. Oliveira (soares@ppgia.pucpr.br)2, Robert Sabourin (robert.sabourin@etsmtl.ca)3


1HSBC Bank, Curitiba, Pr, Brasil
2Universidade Tuitui do Parana, Curitiba, PR, Brasil
3Ecole de Technologie Superieure, Montreal, QC, Canada

This paper appears in: Revista IEEE América Latina

Publication Date: Dec. 2005
Volume: 3,   Issue: 5 
ISSN: 1548-0992


Abstract:
In this paper we propose a strategy to create ensemble of classifiers based on unsupervised features selection. It takes into account a hierarchical multi-objective genetic algorithm that generates a set of classifiers by performing feature selection and then combines them to provide a set of powerful ensembles. The proposed method is evaluated in the context of handwritten month word recognition, using three different feature sets and Hidden Markov Models as classifiers. Comprehensive experiments demonstrate the effectiveness of the proposed strategy.

Index Terms:
Ensemble of Classifiers, Unsupervised Feature Selection, Handwriting Recognition.   


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