Core-generating approximate minimum entropy discretization for rough set feature selection in pattern classification

International Journal of Approximate Reasoning

Volumn 52, Issue 6, 2011, Pages 863-880

  Tian, David ^a,b   Zeng, Xiao Jun ^b   Keane, John ^b  

^a SHEFFIELD HALLAM UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Constraint satisfaction optimization problems; Core generating approximate minimum entropy discretization; Pattern classification; Rough set feature selection

Indexed keywords

BOOLEAN REASONING; CLASSIFICATION POWER; CLASSIFIER PERFORMANCE; CONTINUOUS ATTRIBUTE; CORE SIZE; DATA SETS; DISCRETE ATTRIBUTES; DISCRETIZATION ALGORITHMS; DISCRETIZATION METHOD; DISCRETIZATIONS; EMPTY CORE; FEATURE SELECTION; FEATURE SUBSET; K-NEAREST NEIGHBOURS; MINIMUM ENTROPY; MULTI-LAYER PERCEPTRONS; OPTIMIZATION PROBLEMS; PATTERN CLASSIFICATION; PERFORMANCE ANALYSIS; PERFORMANCE EVALUATION; RBF NETWORK; REDUCTS; ROUGH SET; UCI MACHINE LEARNING REPOSITORY; UPPER BOUND;

ALGORITHMS; DISCRETE EVENT SIMULATION; ENTROPY; FEATURE EXTRACTION; OPTIMIZATION; PATTERN RECOGNITION SYSTEMS; ROUGH SET THEORY; VOLUME MEASUREMENT;

CLASSIFICATION (OF INFORMATION);

EID: 79955557689     PISSN: 0888613X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijar.2011.03.001     Document Type: Article

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