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Volumn 30, Issue 2, 2006, Pages 73-77

A support vector machine using the lazy learning approach for multi-class classification

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY SETS; LINEAR EQUATIONS; NONLINEAR PROGRAMMING; STATISTICAL METHODS;

EID: 33645010982     PISSN: 03091902     EISSN: None     Source Type: Journal    
DOI: 10.1080/03091900500095729     Document Type: Article
Times cited : (2)

References (13)
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    • Transductive inference for text classification using support vector machines
    • Paper presented, Bled, Slovenia, 27-30 June 1999
    • Joachims, T., 1999, Transductive inference for text classification using support vector machines. Paper presented at the International Conference on Machine Learning (ICML), Bled, Slovenia, 27-30 June 1999, pp. 200-209.
    • (1999) International Conference on Machine Learning (ICML) , pp. 200-209
    • Joachims, T.1
  • 5
    • 0002229304 scopus 로고    scopus 로고
    • Pairwise classification and support vector machines
    • B. Schölkopf, C.J.C. Burges and A.J. Smola (Eds). Cambridge, MA: MIT Press
    • Krebel, U.H.G., 1999, Pairwise classification and support vector machines. In B. Schölkopf, C.J.C. Burges and A.J. Smola (Eds) Advances in Kernel Methods: Support vector learning (Cambridge, MA: MIT Press), pp. 255-268.
    • (1999) Advances in Kernel Methods: Support Vector Learning , pp. 255-268
    • Krebel, U.H.G.1
  • 6
  • 8
    • 0037922094 scopus 로고    scopus 로고
    • Fuzzy support vector machines for multiclass problems
    • Paper presented, Bruges, Belgium, 24-26 April 2002
    • Abe, S. and Inoue, T., 2002, Fuzzy support vector machines for multiclass problems. Paper presented at the European Symposium on Artificial Neural Networks (ESANN), Bruges, Belgium, 24-26 April 2002, pp. 113-118.
    • (2002) European Symposium on Artificial Neural Networks (ESANN) , pp. 113-118
    • Abe, S.1    Inoue, T.2
  • 9
    • 0038355084 scopus 로고    scopus 로고
    • Fuzzy least squares support vector machines for multi-class problems
    • Tsujinishi, D. and Abe, S., 2003, Fuzzy least squares support vector machines for multi-class problems. Neural Networks Field, 16, 785-792.
    • (2003) Neural Networks Field , vol.16 , pp. 785-792
    • Tsujinishi, D.1    Abe, S.2
  • 10
    • 0035754859 scopus 로고    scopus 로고
    • SVM Binary classifier ensembles for image classification
    • Paper presented, Atlanta, Georgia, 5-10 November 2001
    • Goh, K.-S., Chang, E. and Cheng, K.T., 2001, SVM Binary classifier ensembles for image classification. Paper presented at CIKM'01, Atlanta, Georgia, 5-10 November 2001, pp. 395-402.
    • (2001) CIKM'01 , pp. 395-402
    • Goh, K.-S.1    Chang, E.2    Cheng, K.T.3
  • 11
    • 0035400665 scopus 로고    scopus 로고
    • The local paradigm for modeling and control: From neuro-fuzzy to lazy learning
    • Bontempi, G., Bersini, H. and Birattari, M., 2001, The local paradigm for modeling and control: from neuro-fuzzy to lazy learning. Fuzzy Sets and Systems, 121, 59-72.
    • (2001) Fuzzy Sets and Systems , vol.121 , pp. 59-72
    • Bontempi, G.1    Bersini, H.2    Birattari, M.3
  • 12
    • 84901251330 scopus 로고    scopus 로고
    • Recursive lazy learning for modeling and control
    • Paper presented, Chemnitz, Germany, 21-23 April 1998
    • Bontempi, G., Bersini, H. and Birattari, M., 1998, Recursive lazy learning for modeling and control. Paper presented at the 10th European Conference on Machine Learning (ECML-98), Chemnitz, Germany, 21-23 April 1998, pp. 292-303.
    • (1998) 10th European Conference on Machine Learning (ECML-98) , pp. 292-303
    • Bontempi, G.1    Bersini, H.2    Birattari, M.3
  • 13
    • 0034171891 scopus 로고    scopus 로고
    • Identifying the impact of decision variables for non-linear classification tasks
    • Kim, S.H. and Shin, S.W., 2000, Identifying the impact of decision variables for non-linear classification tasks. Expert Systems with Applications, 18, 201-214.
    • (2000) Expert Systems with Applications , vol.18 , pp. 201-214
    • Kim, S.H.1    Shin, S.W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.