Iterative feature perturbation as a gene selector for microarray data

International Journal of Pattern Recognition and Artificial Intelligence

Volumn 26, Issue 5, 2012, Pages

  Canul Reich, Juana ^a   Hall, Lawrence O ^a   Goldgof, Dmitry B ^a   Korecki, John N ^a   Eschrich, Steven ^b  

^a University of South Florida   (United States)

^b H LEE MOFFITT CANCER CENTER AND RESEARCH INSTITUTE   (United States)

Author keywords

feature perturbation; Feature selection; gene selection; microarray analysis; t test

Indexed keywords

BASE CLASSIFIERS; CLASSIFICATION ACCURACY; CLASSIFICATION TASKS; COLON CANCER; DATA SETS; DIMENSIONALITY REDUCTION; FEATURE PERTURBATION; FEATURE SETS; GENE SELECTION; GENE SETS; LINEAR SUPPORT VECTOR MACHINES; LUNG CANCER; MICROARRAY ANALYSIS; MICROARRAY DATA; MICROARRAY DATA SETS; NUMBER OF SAMPLES; P-VALUES; PERFORMANCE IMPROVEMENTS; PERTURBATION METHOD; PRE-SELECTION; SUPPORT VECTOR; SVM-RFE; T-TEST;

DATA REDUCTION; DISEASES; EXPERIMENTS; FEATURE EXTRACTION; ITERATIVE METHODS; STATISTICAL TESTS; SUPPORT VECTOR MACHINES;

GENE EXPRESSION;

EID: 84870512015     PISSN: 02180014     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218001412600038     Document Type: Article

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