Supervised hybrid feature selection based on PSO and rough sets for medical diagnosis

Computer Methods and Programs in Biomedicine

Volumn 113, Issue 1, 2014, Pages 175-185

  Inbarani, H Hannah ^a   Azar, Ahmad Taher ^b   Jothi, G ^c  

^a PERIYAR UNIVERSITY   (India)

^b Benha University ^*  (Egypt)

^c SONA COLLEGE OF TECHNOLOGY   (India)

Author keywords

Feature Selection (FS); Particle Swarm Optimization (PSO); Quick Reduct; Relative Reduct; Rough sets

Indexed keywords

DIAGNOSIS; LARGE DATASET; PARTICLE SWARM OPTIMIZATION (PSO); ROUGH SET THEORY;

FEATURE SELECTION METHODS; HYBRID FEATURE SELECTIONS; PREDICTIVE ACCURACY; PROMINENT FEATURES; QUICK REDUCT; REDUNDANT FEATURES; RELATIVE REDUCT; SELECTION TECHNIQUES;

FEATURE EXTRACTION; PARTICLE SWARM OPTIMIZATION (PSO);

ALGORITHM; ARTICLE; DATA MINING; DIAGNOSIS; HUMAN; HYBRIDIZATION; MACHINE LEARNING; MATHEMATICAL COMPUTING; MEDICAL INFORMATION SYSTEM; MEDICAL RESEARCH; PARTICLE SWARM OPTIMIZATION; ROUGH SET; ACCURACY; BREAST CANCER; DIAGNOSTIC PROCEDURE; DIFFERENTIAL DIAGNOSIS; DISEASE CLASSIFICATION; HYBRID; METHODOLOGY; SUPERVISED QUICK REDUCT; SUPERVISED RELATIVE REDUCT;

FEATURE SELECTION (FS); PARTICLE SWARM OPTIMIZATION (PSO); QUICK REDUCT; RELATIVE REDUCT; ROUGH SETS;

DIAGNOSIS; MODELS, THEORETICAL;

EID: 84887826239     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2013.10.007     Document Type: Article

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