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Volumn 2, Issue , 2010, Pages

A novel support vector machine algorithm for solving nonlinear regression problems based on symmetrical points

Author keywords

Regression problems; SVM; Symmetrical points

Indexed keywords

DECISION FUNCTIONS; MODEL OUTPUTS; NONLINEAR REGRESSION PROBLEMS; REGRESSION PROBLEM; SUPPORT VECTOR; SUPPORT VECTOR MACHINE ALGORITHM; SUPPORT VECTOR REGRESSIONS; SVM; SYMMETRICAL POINTS; TRAINING SETS;

EID: 77958058882     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCET.2010.5485250     Document Type: Conference Paper
Times cited : (5)

References (14)
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  • 7
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  • 8
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • Schölkopf, B., Burges, C.J.C., Smola, A.J. Eds., Cambridge, MA: MIT Press
    • J. C. Platt, "Fast training of support vector machines using sequential minimal optimization," In Advances in Kernel Methods: Support Vector Machines, Schölkopf, B., Burges, C.J.C., Smola, A.J. Eds., Cambridge, MA: MIT Press, 1998.
    • (1998) Advances in Kernel Methods: Support Vector Machines
    • Platt, J.C.1
  • 9
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    • Schölkopf, B., Burges, C.J.C., Smola, A.J. Eds., Cambridge, MA: MIT Press
    • T. Joachims, "Making large-scale SVM learning practical," In Advances in Kernel Methods: Support Vector Machines, Schölkopf, B., Burges, C.J.C., Smola, A.J. Eds., Cambridge, MA: MIT Press, 1998.
    • (1998) Advances in Kernel Methods: Support Vector Machines
    • Joachims, T.1
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    • Hsu, C.W.1    Lin, C.J.2
  • 13
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    • Global convergence of SMO algorithm for support vector regression
    • June
    • N. Takahashi, J. Guo, and T. Nishi, "Global Convergence of SMO Algorithm for Support Vector Regression," IEEE Trans. on Neural Networks, vol. 19, no. 6, pp. 971-982, June 2008.
    • (2008) IEEE Trans. on Neural Networks , vol.19 , Issue.6 , pp. 971-982
    • Takahashi, N.1    Guo, J.2    Nishi, T.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.