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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Combining Feature Subsets in Feature Selection
verfasst von : Marina Skurichina, Robert P. W. Duin
Erschienen in: Multiple Classifier Systems
Verlag: Springer Berlin Heidelberg
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In feature selection, a part of the features is chosen as a new feature subset, while the rest of the features is ignored. The neglected features still, however, may contain useful information for discriminating the data classes. To make use of this information, the combined classifier approach can be used. In our paper we study the efficiency of combining applied on top of feature selection/extraction. As well, we analyze conditions when combining classifiers on multiple feature subsets is more beneficial than exploiting a single selected feature set.