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General framework for class-specific feature selection
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DOI：10.1016/j.eswa.2011.02.016.png)
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摘要
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Commonly, when a feature selection algorithm is applied, a single feature subset is selected for all the classes, but this subset could be inadequate for some classes. Class-specific feature selection allows selecting a possible different feature subset for each class. However, all the class-specific feature selection algorithms have been proposed for a particular classifier, which reduce their applicability. In this paper, a general framework for using any traditional feature selector for doing class-specific feature selection, which allows using any classifier, is proposed. Experimental results and a comparison against traditional feature selectors showing the suitability of the proposed framework are included. (c) 2011 Elsevier Ltd. All rights reserved.
Keyword:
Class-specific feature selection
Feature selection
Supervised classification
Classifier ensemble
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7.5
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2.9W
被引数:
10.2W
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