Hybrid genetic algorithms for feature selection

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 26, Issue 11, 2004, Pages 1424-1437

  Oh, Il Seok ^a   Lee, Jin Seon ^b   Moon, Byung Ro ^c  

^a Chonbuk National University   (South Korea)

^b Woosuk University   (South Korea)

^c Seoul National University   (South Korea)

Author keywords

Atomic operation; Feature selection; Hybrid genetic algorithm; Local search operation; Multistart algorithm; Sequential search algorithm

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; GENETIC ALGORITHMS; OPTIMIZATION; SET THEORY;

ATOMIC OPERATION; FEATURE SELECTION; HYBRID GENETIC ALGORITHM; LOCAL SEARCH OPERATION; MULTISTART ALGORITHM; SEQUENTIAL SEARCH ALGORITHM;

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, BIOLOGICAL; MODELS, STATISTICAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE;

EID: 12844260916     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2004.105     Document Type: Article

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