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Volumn , Issue , 2004, Pages 377-384

A theoretical characterization of linear SVM-based feature selection

Author keywords

[No Author keywords available]

Indexed keywords

ARRAY GENE EXPRESSION DOMAIN; MICROARRAYS; MULTIVARIATE LINEAR REGRESSION MODEL; SUPPORT VECTOR MACHINE (SVM);

EID: 14344264951     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (49)

References (16)
  • 3
    • 84899002142 scopus 로고    scopus 로고
    • Uniqueness of the SVM solution
    • Surges, C. J. C., & Crisp, D. J. (2000). Uniqueness of the SVM solution. NIPS (pp. 223-229).
    • (2000) NIPS , pp. 223-229
    • Surges, C.J.C.1    Crisp, D.J.2
  • 7
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002). Gene selection for cancer classification using support vector machines. Machine Learning, 46, 389-422.
    • (2002) Machine Learning , vol.46 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 8
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • Kohavi, R., & John, G. H. (1997). Wrappers for feature subset selection. Artificial Intelligence, 97, 273-324.
    • (1997) Artificial Intelligence , vol.97 , pp. 273-324
    • Kohavi, R.1    John, G.H.2
  • 9
    • 0003357515 scopus 로고    scopus 로고
    • Maximal margin perceptron
    • The MIT Press, Cambridge Massachusetts
    • Kowalczyk, A. (2000). Maximal margin perceptron. Advances in Large Margin Classifiers. The MIT Press, Cambridge Massachusetts.
    • (2000) Advances in Large Margin Classifiers
    • Kowalczyk, A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.