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Volumn 2527, Issue , 2002, Pages 411-419

Convex hull in feature space for support vector machines

Author keywords

[No Author keywords available]

Indexed keywords

BINARY PATTERN RECOGNITION; CONVEX HULL; DATA POINTS; EXTREME POINTS; FEATURE SPACE; GEOMETRIC PROPERTIES; KERNEL FUNCTION; LARGE DATASETS; SUPPORT VECTOR;

EID: 79952262111     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/3-540-36131-6_42     Document Type: Conference Paper
Times cited : (23)

References (13)
  • 2
    • 34249753618 scopus 로고
    • Support vector networks
    • C. Cortes and V. Vapnik. Support vector networks. Machine Learning, 20:273-297, 1995.
    • (1995) Machine Learning , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 6
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • C. Burges. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2(2):121-167, 1998.
    • (1998) Data Mining and Knowledge Discovery , vol.2 , Issue.2 , pp. 121-167
    • Burges, C.1
  • 9
    • 0005154520 scopus 로고    scopus 로고
    • Geometry in learning
    • C. Gorini, E. Hart, W. Meyer, and T. Phillips, editors, Washington, D.C., Mathematical Association of America
    • K. Bennett and E. Bredensteiner. Geometry in learning. In C. Gorini, E. Hart, W. Meyer, and T. Phillips, editors, Geometry at Work, Washington, D.C., 1997. Mathematical Association of America.
    • (1997) Geometry at Work
    • Bennett, K.1    Bredensteiner, E.2
  • 10
    • 0033640690 scopus 로고    scopus 로고
    • A fast iterative nearest point algorithm for support vector machine classifier design
    • S. S. Keerthi, S. K. Shevade, C. Bhattacharyya, and K. R. K. Murthy. A fast iterative nearest point algorithm for support vector machine classifier design. IEEE-NN, 11(1):124, 2000.
    • (2000) IEEE-NN , vol.11 , Issue.1 , pp. 124
    • Keerthi, S.S.1    Shevade, S.K.2    Bhattacharyya, C.3    Murthy, K.R.K.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.