Combating the small sample class imbalance problem using feature selection

IEEE Transactions on Knowledge and Data Engineering

Volumn 22, Issue 10, 2010, Pages 1388-1400

  Wasikowski, Mike ^a   Chen, Xue Wen ^b  

^a Analysis Center   (United States)

^b University of Kansas   (United States)

Author keywords

bioinformatics; Class imbalance problem; feature evaluation and selection; machine learning; pattern recognition; text mining.

Indexed keywords

CLASS IMBALANCE PROBLEMS; FEATURE EVALUATION AND SELECTION; FEATURE SELECTION; IMBALANCED DATA; IMBALANCED DATA SETS; MACHINE-LEARNING; PROBLEM DOMAIN; REAL-WORLD APPLICATION; RECEIVER OPERATING CHARACTERISTICS; RESAMPLING; SIGNAL TO NOISE; SMALL SAMPLES; SPECIFIC PROBLEMS; SUB-OPTIMAL PERFORMANCE; SYSTEMATIC STUDY; TEXT CLASSIFICATION; TEXT MINING;

BIOINFORMATICS; CHARACTER RECOGNITION; CLASSIFICATION (OF INFORMATION); FISHER INFORMATION MATRIX; LEARNING ALGORITHMS; LEARNING SYSTEMS; TEXT PROCESSING;

FEATURE EXTRACTION;

EID: 77956023732     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2009.187     Document Type: Article

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