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
Link To Document :
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