Combined feature selection and cancer prognosis using support vector machine regression

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 8, Issue 6, 2011, Pages 1671-1677

  Sun, Bing Yu ^a   Zhu, Zhi Hua ^b   Li, Jiuyong ^c   Linghu, Bin ^a  

^a INSTITUTE OF INTELLIGENT MACHINES   (China)

^b SUN YAT SEN UNIVERSITY   (China)

^c UNIVERSITY OF SOUTH AUSTRALIA   (Australia)

Author keywords

censored data; Feature selection; Prognostic prediction; support vector machine

Indexed keywords

AUTOMATIC FEATURE SELECTION; CANCER PROGNOSIS; CENSORED DATA; CLASSIFICATION PERFORMANCE; CLASSIFICATION TECHNIQUE; CLINICAL OUTCOME; COMBINED FEATURES; HIGH DIMENSIONAL DATA; MEDICAL DOMAINS; OPTIMIZATION PROBLEMS; PREDICTION METHODS; REAL WORLD DATA; SUPPORT VECTOR; SUPPORT VECTOR MACHINE REGRESSIONS;

FORECASTING; PATIENT TREATMENT; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; VIRTUAL REALITY;

FEATURE EXTRACTION;

ARTICLE; GENE EXPRESSION PROFILING; HUMAN; METHODOLOGY; NEOPLASM; PROGNOSIS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINE;

GENE EXPRESSION PROFILING; HUMANS; NEOPLASMS; PROGNOSIS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

EID: 80052871516     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2010.119     Document Type: Article

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