Unsupervised feature selection for ensemble of classifiers

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Unsupervised feature selection for ensemble of classifiers

Morita, Marisa and Oliveira, Luiz S. and Sabourin, Robert

Proceedings – International Workshop on Frontiers in Handwriting Recognition, IWFHR 2004

Abstract : In this paper we discuss 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 demonstrates the effectiveness of the proposed strategy. © 2004 IEEE.

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