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A filter based feature selection algorithm using null space of covariance matrix for DNA microarray gene expression data

Sharma, Alokanand and Imoto, S. and Miyano, S. (2012) A filter based feature selection algorithm using null space of covariance matrix for DNA microarray gene expression data. Current Bioinformatics, 7 (3). pp. 289-294. ISSN 1574-8936

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    Abstract

    We propose a new filter based feature selection algorithm for classification based on DNA microarray gene expression data. It utilizes null space of covariance matrix for feature selection. The algorithm can perform bulk reduction of features (genes) while maintaining the quality information in the reduced subset of features for discriminative purpose. Thus, it can be used as a pre-processing step for other feature selection algorithms. The algorithm does not assume statistical independency among the features. The algorithm shows promising classification accuracy when compared with other existing techniques on several DNA microarray gene expression datasets.

    Item Type: Journal Article
    Uncontrolled Keywords: Cancer classification, covariance matrix, DNA microarray gene expression data, feature or gene selection, Filter based method, null space, algorithm, Random Forest (RF), support vector machine (SVM), acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML)
    Subjects: T Technology > TA Engineering (General). Civil engineering (General)
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
    Depositing User: Alokanand Sharma
    Date Deposited: 13 Aug 2012 11:23
    Last Modified: 18 Jan 2017 15:23
    URI: http://repository.usp.ac.fj/id/eprint/5033
    UNSPECIFIED

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