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Volumn 4493 LNCS, Issue PART 3, 2007, Pages 486-496

Regularization paths for ν-SVM and ν-SVR

Author keywords

[No Author keywords available]

Indexed keywords

MOTION PLANNING; NEURAL NETWORKS; PARAMETER ESTIMATION;

EID: 38049143933     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-72395-0_62     Document Type: Conference Paper
Times cited : (9)

References (12)
  • 2
    • 76649126602 scopus 로고    scopus 로고
    • Gunter, L., Zhu, J.: Computing the solution path for the regularized support vector regression. In: NIPS. (2005)
    • Gunter, L., Zhu, J.: Computing the solution path for the regularized support vector regression. In: NIPS. (2005)
  • 7
    • 33749254183 scopus 로고    scopus 로고
    • Bach, F., Heckerman, D., Horvitz, E.: On the path to an ideal ROC curve: Considering cost asymmetry in learning classifiers. In Cowell, R.G., Ghahramani, Z., eds.: AISTATS, Society for Artificial Intelligence and Statistics (2005) 9-16
    • Bach, F., Heckerman, D., Horvitz, E.: On the path to an ideal ROC curve: Considering cost asymmetry in learning classifiers. In Cowell, R.G., Ghahramani, Z., eds.: AISTATS, Society for Artificial Intelligence and Statistics (2005) 9-16
  • 8
    • 38049101717 scopus 로고    scopus 로고
    • Wahba, G. In: Support Vector Machines, Reproducing Kernel Hilbert spaces and the randomized GACV. B. Scholkopf and C. Burges and A. Smola edn. MIT Press (1999) 69-88
    • Wahba, G. In: Support Vector Machines, Reproducing Kernel Hilbert spaces and the randomized GACV. B. Scholkopf and C. Burges and A. Smola edn. MIT Press (1999) 69-88
  • 11
    • 0003710388 scopus 로고    scopus 로고
    • Automatic model selection for support vector machines
    • Technical report, Dept. of Computer Science and Information Engineering, National Taiwan University
    • Lee, J.H., Lin, C.J.: Automatic model selection for support vector machines. Technical report, Dept. of Computer Science and Information Engineering, National Taiwan University (2000)
    • (2000)
    • Lee, J.H.1    Lin, C.J.2
  • 12
    • 2542639357 scopus 로고    scopus 로고
    • An efficient method for computing leave-one-out error in support vector machines with gaussian kernels. Neural Networks
    • Lee, M., Keerthi, S., Ong, C.J., DeCoste, D.: An efficient method for computing leave-one-out error in support vector machines with gaussian kernels. Neural Networks, IEEE Transactions 15 (2004) 750- 757
    • (2004) IEEE Transactions , vol.15 , pp. 750-757
    • Lee, M.1    Keerthi, S.2    Ong, C.J.3    DeCoste, D.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.