Recursive mahalanobis separability measure for gene subset selection

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 8, Issue 1, 2011, Pages 266-272

  Mao, Kezhi Z ^a   Tang, Wenyin ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Gene selection; recursive Mahalanobis measure; regularized Mahalanobis measure.

Indexed keywords

2-D SPACE; CLASS SEPARABILITY MEASURE; COMPUTATIONAL OVERHEADS; EXPERIMENTAL STUDIES; EXPRESSION PROBLEM; FEATURE SELECTION; FEATURE SUBSET; GENE EXPRESSION DATA; GENE SELECTION; HIGH DIMENSIONAL SPACES; MAHALANOBIS; OVER FITTING PROBLEM; RECURSIVE APPROACH; RECURSIVE FEATURE ELIMINATION; REGULARIZATION PARAMETERS; SEARCH PROCEDURES; SEPARABILITY MEASURE; SMALL SAMPLE SIZE; SUBSET SELECTION; TEST DATA; TRAINING DATA;

FEATURE EXTRACTION;

GENE EXPRESSION;

ALGORITHM; ARTICLE; BIOLOGY; DATA MINING; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETIC DATABASE; GENETICS; HUMAN; METHODOLOGY; NEOPLASM; REGRESSION ANALYSIS; STATISTICAL ANALYSIS;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATA INTERPRETATION, STATISTICAL; DATA MINING; DATABASES, GENETIC; GENE EXPRESSION PROFILING; HUMANS; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REGRESSION ANALYSIS;

EID: 78449299753     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2010.43     Document Type: Article

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