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Volumn , Issue PART 3, 2013, Pages 2167-2175

Optimizing the F-measure in multi-label classification: Plug-in rule approach versus structured loss minimization

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; LEARNING SYSTEMS; REGRESSION ANALYSIS;

EID: 84897550056     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (50)

References (16)
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    • Chai, K.1
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    • On the consistency of multi-label learning
    • Gao, W. and Zhou, Z. On the consistency of multi-label learning. In COLT, 2011.
    • (2011) COLT
    • Gao, W.1    Zhou, Z.2
  • 6
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    • Efficient max-margin multi-label classification with applications to zero-shot learning
    • Hariharan, B., Vishwanathan, S. V. N., and Varma, M. Efficient max-margin multi-label classification with applications to zero-shot learning. Machine Learning Journal, 88(1):127-155, 2012.
    • (2012) Machine Learning Journal , vol.88 , Issue.1 , pp. 127-155
    • Hariharan, B.1    Vishwanathan, S.V.N.2    Varma, M.3
  • 7
    • 66549104913 scopus 로고    scopus 로고
    • A maximum expected utility framework for binary sequence labeling
    • Jansche, M. A maximum expected utility framework for binary sequence labeling. In ACL 2007, pp. 736-743, 2007.
    • (2007) ACL 2007 , pp. 736-743
    • Jansche, M.1
  • 9
    • 0029193061 scopus 로고
    • Evaluating and optimizing autonomous text classification systems
    • Lewis, D. Evaluating and optimizing autonomous text classification systems. In SIGIR 1995, pp. 246-254, 1995.
    • (1995) SIGIR 1995 , pp. 246-254
    • Lewis, D.1
  • 13
    • 80052965571 scopus 로고    scopus 로고
    • Multilabel classifiers with a probabilistic thresholding strategy
    • Quevedo, J., Luaces, O., and Bahamonde, A. Multilabel classifiers with a probabilistic thresholding strategy. Pattern Recognition, 45, 2012.
    • (2012) Pattern Recognition , pp. 45
    • Quevedo, J.1    Luaces, O.2    Bahamonde, A.3
  • 14
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    • On the consistency of multi-class classification methods
    • May
    • Tewari, A. and Bartlett, P. On the consistency of multi-class classification methods. Journal of Machine Learning Research, 8:1007-1025, May 2007.
    • (2007) Journal of Machine Learning Research , vol.8 , pp. 1007-1025
    • Tewari, A.1    Bartlett, P.2
  • 15
    • 24944537843 scopus 로고    scopus 로고
    • Large margin methods for structured and interdependent output variables
    • Tsochantaridis, I., Joachims, T., Hofmann, T., and Altun, Y. Large margin methods for structured and interdependent output variables. J. Mach. Learn. Res., 6:1453-1484, 2005.
    • (2005) J. Mach. Learn. Res. , vol.6 , pp. 1453-1484
    • Tsochantaridis, I.1    Joachims, T.2    Hofmann, T.3    Altun, Y.4
  • 16
    • 84867119780 scopus 로고    scopus 로고
    • Optimizing F-measures: A tale of two approaches
    • Ye, N., Chai, K., Lee, W., and Chieu, H. Optimizing F-measures: a tale of two approaches. In ICML, 2012.
    • (2012) ICML
    • Ye, N.1    Chai, K.2    Lee, W.3    Chieu, H.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.