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Feature selection in independent component subspace for microarray data classification
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DOI：10.1016/j.neucom.2006.02.006.png)
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Abstract
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A novel method for microarray data classification is proposed in this letter. In this scheme, the sequential floating forward selection (SFFS) technique is used to select the independent components of the DNA microarray data for classification. Experimental results show that the method is efficient and feasible. (c) 2006 Elsevier B.V. All rights reserved.
Keywords:
independent component analysis (ICA)
feature selection
support vector machines (SVM)
gene expression data
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