메뉴 건너뛰기




Volumn 42, Issue 5, 2009, Pages 837-842

Recursive reduced least squares support vector regression

Author keywords

Classification; Iterative strategy; Least squares support vector regression; Parsimoniousness; Reduced technique

Indexed keywords

CURVE FITTING; LEAST SQUARES APPROXIMATIONS; RECURSIVE FUNCTIONS; REGRESSION ANALYSIS;

EID: 58249091399     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.09.028     Document Type: Article
Times cited : (69)

References (32)
  • 2
    • 0032594959 scopus 로고    scopus 로고
    • An overview of statistical learning theory
    • Vapnik V. An overview of statistical learning theory. IEEE Trans. Neural Networks 10 5 (1999) 988-999
    • (1999) IEEE Trans. Neural Networks , vol.10 , Issue.5 , pp. 988-999
    • Vapnik, V.1
  • 3
    • 34249753618 scopus 로고
    • Support vector networks
    • Cortes C., and Vapnik V. Support vector networks. Mach. Learn. 20 (1995) 273-297
    • (1995) Mach. Learn. , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 4
    • 0031334889 scopus 로고    scopus 로고
    • E. Osuna, R. Freund, F. Girosi, An improved training algorithm for support vector machines, in: Proceedings of Neural Networks for Signal Processing, vol. VII, New York, USA, 1997.
    • E. Osuna, R. Freund, F. Girosi, An improved training algorithm for support vector machines, in: Proceedings of Neural Networks for Signal Processing, vol. VII, New York, USA, 1997.
  • 5
    • 58249084095 scopus 로고    scopus 로고
    • J.C. Platt, Fast training of support vector machines using sequential minimal optimization, in: Advances in Kernel Methods-Support Vector Machines, Cambridge, MA, USA, 1998.
    • J.C. Platt, Fast training of support vector machines using sequential minimal optimization, in: Advances in Kernel Methods-Support Vector Machines, Cambridge, MA, USA, 1998.
  • 7
    • 58249089384 scopus 로고    scopus 로고
    • T. Joachims, Making large-scale SVM learning practical, in: Advances in Kernel Methods-Support Vector Machine, Cambridge, MA, USA, 1999.
    • T. Joachims, Making large-scale SVM learning practical, in: Advances in Kernel Methods-Support Vector Machine, Cambridge, MA, USA, 1999.
  • 8
    • 0000913324 scopus 로고    scopus 로고
    • SVMTorch: support vector machines for large-scale regression problems
    • Collobert R., and Bengio S. SVMTorch: support vector machines for large-scale regression problems. J. Mach. Learn. 1 2 (2001) 143-160
    • (2001) J. Mach. Learn. , vol.1 , Issue.2 , pp. 143-160
    • Collobert, R.1    Bengio, S.2
  • 9
    • 58249092708 scopus 로고    scopus 로고
    • C.C. Chang, C.J. Lin, LIBSVM: a library for support vector machines, available from 〈http://www.csie.ntu.edu.tw/~cjlin〉.
    • C.C. Chang, C.J. Lin, LIBSVM: a library for support vector machines, available from 〈http://www.csie.ntu.edu.tw/~cjlin〉.
  • 10
    • 0001260194 scopus 로고    scopus 로고
    • Exact simplification of support vector solutions
    • Downs T., Gates K., and Masters A. Exact simplification of support vector solutions. J. Mach. Learn. 2 2 (2002) 293-297
    • (2002) J. Mach. Learn. , vol.2 , Issue.2 , pp. 293-297
    • Downs, T.1    Gates, K.2    Masters, A.3
  • 11
    • 58249088226 scopus 로고    scopus 로고
    • Y.-J. Lee, O.L. Mangasarian, RSVM: reduced support vector machines, in: Proceedings of the First SIAM International Conference on Data Mining, 2001.
    • Y.-J. Lee, O.L. Mangasarian, RSVM: reduced support vector machines, in: Proceedings of the First SIAM International Conference on Data Mining, 2001.
  • 12
    • 0742321291 scopus 로고    scopus 로고
    • A study on reduced support vector machines
    • Lin K.M., and Lin C.J. A study on reduced support vector machines. IEEE Trans. Neural Networks 14 6 (2003) 1449-1459
    • (2003) IEEE Trans. Neural Networks , vol.14 , Issue.6 , pp. 1449-1459
    • Lin, K.M.1    Lin, C.J.2
  • 13
    • 33846092558 scopus 로고    scopus 로고
    • Reduced support vector machines: a statistical theory
    • Lee Y.J., and Huang S.Y. Reduced support vector machines: a statistical theory. IEEE Trans. Neural Networks 18 1 (2007) 1-13
    • (2007) IEEE Trans. Neural Networks , vol.18 , Issue.1 , pp. 1-13
    • Lee, Y.J.1    Huang, S.Y.2
  • 14
    • 0032638628 scopus 로고    scopus 로고
    • Least squares support vector machine classifiers
    • Suykens J.A.K., and Vandewalle J. Least squares support vector machine classifiers. Neural Process. Lett. 9 3 (1999) 293-300
    • (1999) Neural Process. Lett. , vol.9 , Issue.3 , pp. 293-300
    • Suykens, J.A.K.1    Vandewalle, J.2
  • 17
    • 58249084677 scopus 로고    scopus 로고
    • J.A.K. Suykens, L. Lukas, P. Van Dooren, B. De Moor, J. Vandewalle, Least squares support vector machine classifiers: a large scale algorithm, in: Proceedings of the European Conference on Circuit Theory and Design, Torino, Italy, 1999.
    • J.A.K. Suykens, L. Lukas, P. Van Dooren, B. De Moor, J. Vandewalle, Least squares support vector machine classifiers: a large scale algorithm, in: Proceedings of the European Conference on Circuit Theory and Design, Torino, Italy, 1999.
  • 18
    • 15344351150 scopus 로고    scopus 로고
    • An improved conjugate gradient method scheme to the solution of least squares SVM
    • Chu W., Ong C.J., and Keerthy S.S. An improved conjugate gradient method scheme to the solution of least squares SVM. IEEE Trans. Neural Networks 16 2 (2005) 498-501
    • (2005) IEEE Trans. Neural Networks , vol.16 , Issue.2 , pp. 498-501
    • Chu, W.1    Ong, C.J.2    Keerthy, S.S.3
  • 19
    • 0037313407 scopus 로고    scopus 로고
    • SMO for least squares SVM formulations
    • Keerthi S.S., and Shevade S.K. SMO for least squares SVM formulations. Neural Comput. 15 2 (2003) 487-507
    • (2003) Neural Comput. , vol.15 , Issue.2 , pp. 487-507
    • Keerthi, S.S.1    Shevade, S.K.2
  • 20
    • 85117867000 scopus 로고    scopus 로고
    • J.A.K. Suykens, L. Lukas, J. Vandewalle, Sparse approximation using least square vector machines, in: 2000 IEEE International Symposium on Circuits and Systems, Lausanne, Switzerland, 2000.
    • J.A.K. Suykens, L. Lukas, J. Vandewalle, Sparse approximation using least square vector machines, in: 2000 IEEE International Symposium on Circuits and Systems, Lausanne, Switzerland, 2000.
  • 21
    • 0037507242 scopus 로고    scopus 로고
    • Pruning error minimization in least squares support vector machines
    • de Kruif B.J., and de Vries T.J.A. Pruning error minimization in least squares support vector machines. IEEE Trans. Neural Networks 14 3 (2004) 696-702
    • (2004) IEEE Trans. Neural Networks , vol.14 , Issue.3 , pp. 696-702
    • de Kruif, B.J.1    de Vries, T.J.A.2
  • 22
    • 28244453270 scopus 로고    scopus 로고
    • SMO-based pruning methods for sparse least squares support vector machines
    • Zeng X.Y., and Chen X.W. SMO-based pruning methods for sparse least squares support vector machines. IEEE Trans. Neural Networks 16 6 (2005) 1541-1546
    • (2005) IEEE Trans. Neural Networks , vol.16 , Issue.6 , pp. 1541-1546
    • Zeng, X.Y.1    Chen, X.W.2
  • 23
    • 34047118751 scopus 로고    scopus 로고
    • Comments on "Pruning error minimization in least squares support vector machines"
    • Kuh A., and De Wilde P. Comments on "Pruning error minimization in least squares support vector machines". IEEE Trans. Neural Networks 18 2 (2007) 606-609
    • (2007) IEEE Trans. Neural Networks , vol.18 , Issue.2 , pp. 606-609
    • Kuh, A.1    De Wilde, P.2
  • 24
    • 34248636293 scopus 로고    scopus 로고
    • Fast sparse approximation for least squares support vector machine
    • Jiao L., Bo L., and Wang L. Fast sparse approximation for least squares support vector machine. IEEE Trans. Neural Networks 18 3 (2007) 685-697
    • (2007) IEEE Trans. Neural Networks , vol.18 , Issue.3 , pp. 685-697
    • Jiao, L.1    Bo, L.2    Wang, L.3
  • 25
    • 0036972152 scopus 로고    scopus 로고
    • Reduced rank kernel ridge regression
    • Cawley G.C., and Talbot N.L.C. Reduced rank kernel ridge regression. Neural Process. Lett. 16 3 (2002) 293-302
    • (2002) Neural Process. Lett. , vol.16 , Issue.3 , pp. 293-302
    • Cawley, G.C.1    Talbot, N.L.C.2
  • 27
    • 10044278059 scopus 로고    scopus 로고
    • Y. Zhao, K.C. Keong, Fast leave-one-out evaluation and improvement on inference for LS-SVMs, in: Proceedings of the 17th International Conference on Pattern Recognition, Los Alamitos, CA, USA, 2004.
    • Y. Zhao, K.C. Keong, Fast leave-one-out evaluation and improvement on inference for LS-SVMs, in: Proceedings of the 17th International Conference on Pattern Recognition, Los Alamitos, CA, USA, 2004.
  • 28
    • 34147111649 scopus 로고    scopus 로고
    • Fast cross-validation algorithms for least squares support vector machine and kernel ridge regression
    • An S., Liu W., and Venkatesh S. Fast cross-validation algorithms for least squares support vector machine and kernel ridge regression. Pattern Recognition 40 8 (2007) 2154-2162
    • (2007) Pattern Recognition , vol.40 , Issue.8 , pp. 2154-2162
    • An, S.1    Liu, W.2    Venkatesh, S.3
  • 29
    • 26944501740 scopus 로고    scopus 로고
    • Bias-variance analysis of support vector machines for the development of SVM-based ensemble methods
    • Valentini G., and Dietterich T.G. Bias-variance analysis of support vector machines for the development of SVM-based ensemble methods. J. Mach. Learn. Res. 5 (2004) 725-775
    • (2004) J. Mach. Learn. Res. , vol.5 , pp. 725-775
    • Valentini, G.1    Dietterich, T.G.2
  • 30
    • 0346250790 scopus 로고    scopus 로고
    • Practical selection of SVM parameters and noise estimation for SVM regression
    • Cherkassky V., and Ma Y.Q. Practical selection of SVM parameters and noise estimation for SVM regression. Neural Networks 17 (2004) 113-126
    • (2004) Neural Networks , vol.17 , pp. 113-126
    • Cherkassky, V.1    Ma, Y.Q.2
  • 31
    • 58249089708 scopus 로고    scopus 로고
    • Available from 〈http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/regression.html〉.
    • Available from 〈http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/regression.html〉.
  • 32
    • 58249093319 scopus 로고    scopus 로고
    • Available from 〈http://www.liacc.up.pt/~ltorgo/Regression/DataSets.html〉.
    • Available from 〈http://www.liacc.up.pt/~ltorgo/Regression/DataSets.html〉.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.