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Erschienen in:
2009 | OriginalPaper | Buchkapitel
A Cluster-Based Feature Selection Approach
verfasst von : Thiago F. Covões, Eduardo R. Hruschka, Leandro N. de Castro, Átila M. Santos
Erschienen in: Hybrid Artificial Intelligence Systems
Verlag: Springer Berlin Heidelberg
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This paper proposes a filter-based method for feature selection. The filter is based on the partitioning of the feature space into clusters of similar features. The number of clusters and, consequently, the cardinality of the subset of selected features, is automatically estimated from the data. Empirical results illustrate the performance of the proposed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to a state of the art algorithm for feature selection, but with more modest computing time requirements.