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Volumn , Issue , 2003, Pages 996-999

A Feature Selection Method Based on Minimizing Generalization Bounds of SVM via GA

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; ERROR ANALYSIS; GENETIC ALGORITHMS; PROBABILITY DENSITY FUNCTION; REGRESSION ANALYSIS;

EID: 0345528231     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/isic.2003.1254773     Document Type: Conference Paper
Times cited : (6)

References (7)
  • 2
    • 85089251671 scopus 로고    scopus 로고
    • Comparison of classfier methods: A case study in handwriting digit recognition
    • IEEE Compute Society Press, Los Alamos, California
    • th IAPR International Conference on Pattern Recognition, 2, IEEE Compute Society Press, Los Alamos, California, pp.77-83.
    • th IAPR International Conference on Pattern Recognition , vol.2 , pp. 77-83
    • Bottou, L.1
  • 4
    • 0024895461 scopus 로고
    • A note on genetic algorithm for large-scale feature selection
    • W. Siedlecki and J. Sklansky, "A note on genetic algorithm for large-scale feature selection," Pattern Recognition Letters, 1989, vol.10, pp.335-347.
    • (1989) Pattern Recognition Letters , vol.10 , pp. 335-347
    • Siedlecki, W.1    Sklansky, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.