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Volumn 24, Issue 11, 2012, Pages 2825-2851

Adaptive metric learning vector quantization for ordinal classification

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; LEARNING; NONLINEAR SYSTEM;

EID: 84874197542     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/NECO_a_00358     Document Type: Article
Times cited : (23)

References (20)
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  • 3
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  • 6
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    • Asimple approach to ordinal classification
    • New York: Springer-Verlag. Learning Vector Quantization for Ordinal Classification 2851
    • Frank, E.,&Hall, M. (2001).Asimple approach to ordinal classification. In Proceedings of the 12th European Conference on Machine Learning (pp. 145-156). New York: Springer-Verlag. Learning Vector Quantization for Ordinal Classification 2851
    • (2001) Proceedings of the 12th European Conference on Machine Learning , pp. 145-156
    • Frank, E.1    Hall, M.2
  • 8
    • 0036791938 scopus 로고    scopus 로고
    • Generalized relevance learning vector quantization
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    • (2002) Neural Networks , vol.15 , pp. 1059-1068
    • Hammer, B.1    Villmann, T.2
  • 9
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    • (1998)
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  • 10
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    • (Tech. Rep. No. TKKF-A601). Espoo, Finland: Laboratory of Computer and Information Science, Department of Technical Physics, Helsinki University of Technology
    • Kohonen, T. (1986). Learning vector quantization for pattern recognition (Tech. Rep. No. TKKF-A601). Espoo, Finland: Laboratory of Computer and Information Science, Department of Technical Physics, Helsinki University of Technology.
    • (1986) Learning vector quantization for pattern recognition
    • Kohonen, T.1
  • 12
    • 39649107920 scopus 로고    scopus 로고
    • Ordinal regression by extended binary classification
    • In B. Scḧolkopf, J. C. Platt, & T. Hofmann (Eds.), MA: MIT Press
    • Li, L., & Lin, H. (2007). Ordinal regression by extended binary classification. In B. Scḧolkopf, J. C. Platt, & T. Hofmann (Eds.), Advances in neural information processing systems, 19 (pp. 865-872). Cambridge, MA: MIT Press.
    • (2007) Advances in neural information processing systems Cambridge , vol.19 , pp. 865-872
    • Li, L.1    Lin, H.2
  • 13
    • 84861176005 scopus 로고    scopus 로고
    • Reduction from cost-sensitive ordinal ranking to weighted binary classification
    • Lin, H., & Li, L. (2012). Reduction from cost-sensitive ordinal ranking to weighted binary classification. Neural Computation, 24, 1329-1367.
    • (2012) Neural Computation , vol.24 , pp. 1329-1367
    • Lin, H.1    Li, L.2
  • 14
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    • Generalized learning vector quantization
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    • Sato, A.,&Yamada,K. (1996).Generalized learning vector quantization. In D. Touretzky, M. Mozer, & M. E. Hasselmo (Eds.) Advances in neural information processing systems, 8 (pp. 423-429). Cambridge, MA: MIT Press.
    • (1996) Advances in neural information processing systems Cambridge , vol.8 , pp. 423-429
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