Improved sparse multi-class SVM and its application for gene selection in cancer classification

Cancer Informatics

Volumn 12, Issue , 2013, Pages 143-153

  Hhuang, Lingkang ^a,b,c   Zhang, Hhao Hhelen ^b,d   Zeng, Zhao Bang ^b   Bushel, Pierre Rr ^c  

^a GLAXOSMITHKLINE   (United States)

^b NORTH CAROLINA STATE UNIVERSITY   (United States)

^c NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES   (United States)

^d University of Arizona   (United States)

Author keywords

Cancer classification; Classification; Microarray; Multi class SVM; Shrinkage methods; Support vector machine (SVM); Variable selection

Indexed keywords

ACCESS TO INFORMATION; ACCURACY; ARTICLE; BAYES THEOREM; CANCER CLASSIFICATION; GENE EXPRESSION; GENETIC SELECTION; HUMAN; INFORMATION PROCESSING; INTERNET; MATHEMATICAL ANALYSIS; NONLINEAR SYSTEM; SUPPORT VECTOR MACHINE;

EID: 84881281027     PISSN: None     EISSN: 11769351     Source Type: Journal    
DOI: 10.4137/CIN.S10212     Document Type: Article

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