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Volumn 22, Issue 5, 2013, Pages 999-1011

Robust minimum class variance twin support vector machine classifier

Author keywords

Class variance matrices; Machine learning; Nonparallel hyperplanes; Pattern recognition; Twin support vector machine

Indexed keywords

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; PATTERN RECOGNITION; VECTORS;

EID: 84875068950     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-011-0791-3     Document Type: Article
Times cited : (25)

References (38)
  • 4
    • 84957069814 scopus 로고    scopus 로고
    • Text categorization with support vector machines: learning with many relevant features
    • Chemnitz, Germany
    • Joachims T, Ndellec C, Rouveriol C (1998) Text categorization with support vector machines: learning with many relevant features. In: European conference on machine learning No. 10, Chemnitz, Germany, vol. 1398, pp 137-142.
    • (1998) European conference on machine learning , vol.1398 , Issue.1 , pp. 137-142
    • Joachims, T.1    Ndellec, C.2    Rouveriol, C.3
  • 6
    • 0038104242 scopus 로고    scopus 로고
    • Joint time-frequency-space classification of EEG in a brain-computer interface application
    • Ebrahimi T, Garcia GN, Vesin JM (2003) Joint time-frequency-space classification of EEG in a brain-computer interface application. EURASIP J Appl Signal Process 1(7): 713-729.
    • (2003) EURASIP J Appl Signal Process , vol.1 , Issue.7 , pp. 713-729
    • Ebrahimi, T.1    Garcia, G.N.2    Vesin, J.M.3
  • 7
    • 0031375732 scopus 로고    scopus 로고
    • Nonlinear prediction of chaotic time series using a support vector machine
    • Amelia Island, FL
    • Mukherjee S, Osuna E, Girosi F (1997) Nonlinear prediction of chaotic time series using a support vector machine. In: Proceedings of the 1997 IEEE workshop, Amelia Island, FL, pp 511-520.
    • (1997) Proceedings of the 1997 IEEE workshop , pp. 511-520
    • Mukherjee, S.1    Osuna, E.2    Girosi, F.3
  • 9
    • 0035441827 scopus 로고    scopus 로고
    • Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators
    • Williamson RC, Smola AJ, Schölkopf B (2001) Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators. IEEE Trans Inf Theory 47(6): 2516-2532.
    • (2001) IEEE Trans Inf Theory , vol.47 , Issue.6 , pp. 2516-2532
    • Williamson, R.C.1    Smola, A.J.2    Schölkopf, B.3
  • 10
    • 34249753618 scopus 로고
    • Support vector networks
    • Cortes C, Vapnik VN (1995) Support vector networks. Mach Learn 20: 273-297.
    • (1995) Mach Learn , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.N.2
  • 12
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • In: Schölkopf B, Burges CJC, Smola AJ (eds), MIT Press, Cambridge, MA
    • Platt J (1999) Fast training of support vector machines using sequential minimal optimization. In: Schölkopf B, Burges CJC, Smola AJ (eds) Advances in Kernel methods-support vector learning. MIT Press, Cambridge, MA, pp 185-2008.
    • (1999) Advances in Kernel methods-support vector learning , pp. 185-2008
    • Platt, J.1
  • 13
    • 0033640690 scopus 로고    scopus 로고
    • A fast iterative nearest point algorithm for support vector machine classifier design
    • Keerthi SS, Shevade SK, Bhattacharyya C, Murthy KRK (2000) A fast iterative nearest point algorithm for support vector machine classifier design. IEEE Trans Neural Netw 11(1): 124-136.
    • (2000) IEEE Trans Neural Netw , vol.11 , Issue.1 , pp. 124-136
    • Keerthi, S.S.1    Shevade, S.K.2    Bhattacharyya, C.3    Murthy, K.R.K.4
  • 14
    • 2942586739 scopus 로고    scopus 로고
    • A generalized S-K algorithm for learning ν-SVM classifiers
    • Tao Q, Wu GW, Wang J (2004) A generalized S-K algorithm for learning ν-SVM classifiers. Pattern Recogn Lett 25(10): 1165-1171.
    • (2004) Pattern Recogn Lett , vol.25 , Issue.10 , pp. 1165-1171
    • Tao, Q.1    Wu, G.W.2    Wang, J.3
  • 15
    • 0032638628 scopus 로고    scopus 로고
    • Least squares support vector machine classifiers
    • Suykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9(3): 293-300.
    • (1999) Neural Process Lett , vol.9 , Issue.3 , pp. 293-300
    • Suykens, J.A.K.1    Vandewalle, J.2
  • 18
    • 0036505650 scopus 로고    scopus 로고
    • Fuzzy support vector machines
    • Lin C-F, Wang S-D (2003) Fuzzy support vector machines. IEEE Trans Neural Netw 13(2): 464-471.
    • (2003) IEEE Trans Neural Netw , vol.13 , Issue.2 , pp. 464-471
    • Lin, C.-F.1    Wang, S.-D.2
  • 19
    • 21844440579 scopus 로고    scopus 로고
    • Core vector machines: fast SVM training on very large data sets
    • Tsang IW, Kwok JT, Cheung P-M (2005) Core vector machines: fast SVM training on very large data sets. J Mach Learn Res 6: 363-392.
    • (2005) J Mach Learn Res , vol.6 , pp. 363-392
    • Tsang, I.W.1    Kwok, J.T.2    Cheung, P.-M.3
  • 21
    • 33644830072 scopus 로고    scopus 로고
    • Multisurface proximal support vector classification via generalized eigenvalues
    • Mangasarian OL, Wild EW (2006) Multisurface proximal support vector classification via generalized eigenvalues. IEEE Trans Pattern Anal Mach Intell 28(1): 69-74.
    • (2006) IEEE Trans Pattern Anal Mach Intell , vol.28 , Issue.1 , pp. 69-74
    • Mangasarian, O.L.1    Wild, E.W.2
  • 22
    • 34047225880 scopus 로고    scopus 로고
    • Twin support vector machines for pattern classification
    • Jayadeva, Khemchandani R, Chandra S (2007) Twin support vector machines for pattern classification. IEEE Trans Pattern Anal Mach Intell 29(5): 905-910.
    • (2007) IEEE Trans Pattern Anal Mach Intell , vol.29 , Issue.5 , pp. 905-910
    • Jayadeva, K.R.1    Chandra, S.2
  • 23
    • 79957988400 scopus 로고    scopus 로고
    • Improvements on twin support vector machines
    • Shao Y, Zhang C, Wang X, Deng N (2011) Improvements on twin support vector machines. IEEE Trans Neural Netw 22(6): 962-968.
    • (2011) IEEE Trans Neural Netw , vol.22 , Issue.6 , pp. 962-968
    • Shao, Y.1    Zhang, C.2    Wang, X.3    Deng, N.4
  • 24
    • 60249095678 scopus 로고    scopus 로고
    • Least squares twin support vector machines for pattern classification
    • Kumar MA, Gopal M (2009) Least squares twin support vector machines for pattern classification. Expert Syst Appl 36: 7535-7543.
    • (2009) Expert Syst Appl , vol.36 , pp. 7535-7543
    • Kumar, M.A.1    Gopal, M.2
  • 25
    • 48649097170 scopus 로고    scopus 로고
    • Application of smoothing technique on twin support vector machines
    • Kumar MA, Gopal M (2008) Application of smoothing technique on twin support vector machines. Pattern Recogn Lett 29: 1842-1848.
    • (2008) Pattern Recogn Lett , vol.29 , pp. 1842-1848
    • Kumar, M.A.1    Gopal, M.2
  • 26
    • 57749189368 scopus 로고    scopus 로고
    • Nonparallel plane proximal classifier
    • Ghorai S, Mukherjee A, Dutta PK (2009) Nonparallel plane proximal classifier. Signal Process 89(4): 510-522.
    • (2009) Signal Process , vol.89 , Issue.4 , pp. 510-522
    • Ghorai, S.1    Mukherjee, A.2    Dutta, P.K.3
  • 27
    • 69249202291 scopus 로고    scopus 로고
    • Newton's method for nonparallel plane proximal classifier with unity norm hyperplanes
    • Ghorai S, Dutta PK, Mukherjee A (2010) Newton's method for nonparallel plane proximal classifier with unity norm hyperplanes. Signal Process 90(1): 93-104.
    • (2010) Signal Process , vol.90 , Issue.1 , pp. 93-104
    • Ghorai, S.1    Dutta, P.K.2    Mukherjee, A.3
  • 28
    • 76849100708 scopus 로고    scopus 로고
    • TSVR: an efficient twin support vector machine for regression
    • Peng X (2010) TSVR: an efficient twin support vector machine for regression. Neural Netw 23(3): 365-372.
    • (2010) Neural Netw , vol.23 , Issue.3 , pp. 365-372
    • Peng, X.1
  • 29
    • 78649962833 scopus 로고    scopus 로고
    • Primal twin support vector regression and its sparse approximation
    • Peng X (2010) Primal twin support vector regression and its sparse approximation. Neurocomputing 73(16-18): 2846-2858.
    • (2010) Neurocomputing , vol.73 , Issue.16-18 , pp. 2846-2858
    • Peng, X.1
  • 31
    • 0035394251 scopus 로고    scopus 로고
    • Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication
    • Tefas A, Kotropoulos C, Pitas I (2001) Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication. IEEE Trans Pattern Anal Mach Intell 23(7): 735-746.
    • (2001) IEEE Trans Pattern Anal Mach Intell , vol.23 , Issue.7 , pp. 735-746
    • Tefas, A.1    Kotropoulos, C.2    Pitas, I.3
  • 32
    • 0038633559 scopus 로고    scopus 로고
    • Constructing descriptive and discriminative nonlinear features: Ayleigh coefficients in Kernel feature spaces
    • Mika S, Ratsch G, Weston J, Schölkopf B, Smola A, Muller K-R (2003) Constructing descriptive and discriminative nonlinear features: Ayleigh coefficients in Kernel feature spaces. IEEE Trans Pattern Anal Mach Intell 25(5): 623-628.
    • (2003) IEEE Trans Pattern Anal Mach Intell , vol.25 , Issue.5 , pp. 623-628
    • Mika, S.1    Ratsch, G.2    Weston, J.3    Schölkopf, B.4    Smola, A.5    Muller, K.-R.6
  • 34
    • 34648814107 scopus 로고    scopus 로고
    • Minimum class variance support vector machines
    • Zafeiriou S, Tefas A, Pitas I (2007) Minimum class variance support vector machines. IEEE Trans Image Process 16(10): 2551-2564.
    • (2007) IEEE Trans Image Process , vol.16 , Issue.10 , pp. 2551-2564
    • Zafeiriou, S.1    Tefas, A.2    Pitas, I.3
  • 35
    • 0035789613 scopus 로고    scopus 로고
    • Proximal support vector machines
    • San Francisco
    • Fung G, Mangasarian OL (2001) Proximal support vector machines. In: Proceedings of KDD-2001, San Francisco, pp 77-86.
    • (2001) Proceedings of KDD-2001 , pp. 77-86
    • Fung, G.1    Mangasarian, O.L.2
  • 37
    • 33745834241 scopus 로고    scopus 로고
    • University of California, Department of Information and Computer Sciences, Irvine, CA. On-line at:
    • Blake CI, Merz CJ (1998) UCI repository for machine learning databases. University of California, Department of Information and Computer Sciences, Irvine, CA. On-line at: http://www. ics. uci. edu/mlearn/MLRepository. html.
    • (1998) UCI repository for machine learning databases
    • Blake, C.I.1    Merz, C.J.2
  • 38
    • 84875076847 scopus 로고    scopus 로고
    • MATLAB, On-line at:
    • MATLAB, On-line at: http://www. mathworks. com.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.