Title of article
General framework for class-specific feature selection
Author/Authors
Pineda-Bautista، نويسنده , , B?rbara B. and Carrasco-Ochoa، نويسنده , , J.A. and Mart??nez-Trinidad، نويسنده , , J. Fco.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
7
From page
10018
To page
10024
Abstract
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.
Keywords
Supervised classification , Classifier ensemble , Class-specific feature selection , feature selection
Journal title
Expert Systems with Applications
Serial Year
2011
Journal title
Expert Systems with Applications
Record number
2349825
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