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Volumn 5212 LNAI, Issue PART 2, 2008, Pages 390-405

Classification of multi-labeled data: A generative approach

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC FIELDS; ACOUSTICS; DATABASE SYSTEMS; DIAGNOSIS; IMAGE SEGMENTATION; LEARNING SYSTEMS; ROBOT LEARNING;

EID: 56149116656     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87481-2_26     Document Type: Conference Paper
Times cited : (24)

References (14)
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    • Multi-labelled classification using maximum entropy method
    • Zhu, S., Ji, X., Xu, W., Gong, Y.: Multi-labelled classification using maximum entropy method. In: Proceedings of SIGIR 2005 (2005)
    • (2005) Proceedings of SIGIR
    • Zhu, S.1    Ji, X.2    Xu, W.3    Gong, Y.4
  • 4
    • 0000406788 scopus 로고
    • Solving multiclass learning problems via error-correcting output codes
    • Dietterich, T.G., Bakiri, G.: Solving multiclass learning problems via error-correcting output codes. J. of Articificial Intelligence Research 2, 263-286 (1995)
    • (1995) J. of Articificial Intelligence Research , vol.2 , pp. 263-286
    • Dietterich, T.G.1    Bakiri, G.2
  • 5
    • 84943242305 scopus 로고    scopus 로고
    • Clare, A., King, R.D.: Knowledge discovery in multi-label phenotype data. In: Siebes, A., De Raedt, L. (eds.) PKDD 2001. LNCS (LNAI), 2168, pp. 42-53. Springer, Heidelberg (2001)
    • Clare, A., King, R.D.: Knowledge discovery in multi-label phenotype data. In: Siebes, A., De Raedt, L. (eds.) PKDD 2001. LNCS (LNAI), vol. 2168, pp. 42-53. Springer, Heidelberg (2001)
  • 6
    • 2542631648 scopus 로고    scopus 로고
    • Kernel methods for multi-labelled classification and categorical regression problems
    • Elisseeff, A., Weston, J.: Kernel methods for multi-labelled classification and categorical regression problems. In: Proceedings of NIPS 2002 (2002)
    • (2002) Proceedings of NIPS
    • Elisseeff, A.1    Weston, J.2
  • 7
    • 56149090148 scopus 로고    scopus 로고
    • Joachims, T.: Text categorization with support vector machines: learning with many relevant features. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, 1398. Springer, Heidelberg (1998)
    • Joachims, T.: Text categorization with support vector machines: learning with many relevant features. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398. Springer, Heidelberg (1998)
  • 8
    • 33847643079 scopus 로고    scopus 로고
    • Multi-label text classification with a mixture model trained by EM
    • McCallum, A.K.: Multi-label text classification with a mixture model trained by EM. In: Proceedings of NIPS 1999 (1999)
    • (1999) Proceedings of NIPS
    • McCallum, A.K.1
  • 10
    • 0031189914 scopus 로고    scopus 로고
    • Multitask learning
    • Caruana, R.: Multitask learning. Machine Learning 28(1), 41-75 (1997)
    • (1997) Machine Learning , vol.28 , Issue.1 , pp. 41-75
    • Caruana, R.1
  • 12
    • 0000800741 scopus 로고
    • A tutorial on hidden markov models and selected applications in speech recognition
    • Rabiner, L.R.: A tutorial on hidden markov models and selected applications in speech recognition. In: Readings in speech recognition, pp. 267-296 (1990)
    • (1990) Readings in speech recognition , pp. 267-296
    • Rabiner, L.R.1
  • 13
    • 56149119326 scopus 로고    scopus 로고
    • Hastie, T., Tibshirani, R.: Discriminant analysis by Gaussian Mixtures. J. of the Royal Statist. Soc. B 58, 155-176 (1996)
    • Hastie, T., Tibshirani, R.: Discriminant analysis by Gaussian Mixtures. J. of the Royal Statist. Soc. B 58, 155-176 (1996)
  • 14
    • 56149087064 scopus 로고    scopus 로고
    • Dempster, A., Laird, N., Rubin, D.: Maximum likelihood from incomplete data via the EM algorithm. J. of the Royal Statist. Soc. B 39(1), 138 (1977)
    • Dempster, A., Laird, N., Rubin, D.: Maximum likelihood from incomplete data via the EM algorithm. J. of the Royal Statist. Soc. B 39(1), 138 (1977)


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