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Volumn , Issue , 2012, Pages 101-110

Hierarchical multilabel classification with minimum Bayes risk

Author keywords

Bayesian decision theory; Hierarchical classification; Multilabel classification

Indexed keywords

BAYES-OPTIMAL; BAYESIAN DECISION THEORY; GREEDY ALGORITHMS; HIERARCHICAL CLASSIFICATION; HIERARCHICAL MULTI-LABEL CLASSIFICATIONS; LOSS FUNCTIONS; MINIMUM BAYES RISK; MISCLASSIFICATIONS; MULTI-LABEL; MULTI-LABEL CLASSIFICATIONS; MULTIPLE LABELS; REAL WORLD DATA; TREE-STRUCTURED;

EID: 84874081088     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2012.42     Document Type: Conference Paper
Times cited : (26)

References (32)
  • 1
    • 0033905095 scopus 로고    scopus 로고
    • BoosTexter: A boosting-based system for text categorization
    • R. Schapire and Y. Singer, "BoosTexter: A boosting-based system for text categorization," Machine Learning, vol. 39, no. 2, pp. 135-168, 2000.
    • (2000) Machine Learning , vol.39 , Issue.2 , pp. 135-168
    • Schapire, R.1    Singer, Y.2
  • 2
    • 33947681316 scopus 로고    scopus 로고
    • ML-KNN: A lazy learning approach to multi-label learning
    • M.-L. Zhang and Z.-H. Zhou, "ML-KNN: A lazy learning approach to multi-label learning," Pattern Recognition, vol. 40, no. 7, pp. 2038-2048, 2007.
    • (2007) Pattern Recognition , vol.40 , Issue.7 , pp. 2038-2048
    • Zhang, M.-L.1    Zhou, Z.-H.2
  • 4
    • 52949141834 scopus 로고    scopus 로고
    • Decision trees for hierarchical multi-label classification
    • C. Vens, J. Struyf, L. Schietgat, S. Džeroski, and H. Blockeel, "Decision trees for hierarchical multi-label classification," Machine Learning, vol. 73, no. 2, pp. 185-214, 2008.
    • (2008) Machine Learning , vol.73 , Issue.2 , pp. 185-214
    • Vens, C.1    Struyf, J.2    Schietgat, L.3    Džeroski, S.4    Blockeel, H.5
  • 5
    • 78651375098 scopus 로고    scopus 로고
    • A survey of hierarchical classification across different application domains
    • Jan
    • C. Silla and A. Freitas, "A survey of hierarchical classification across different application domains," Data Mining and Knowledge Discovery, vol. 22, no. 1-2, pp. 1-42, Jan. 2010.
    • (2010) Data Mining and Knowledge Discovery , vol.22 , Issue.1-2 , pp. 1-42
    • Silla, C.1    Freitas, A.2
  • 12
    • 33645323768 scopus 로고    scopus 로고
    • Hierarchical multi-label prediction of gene function
    • Z. Barutcuoglu and O. Troyanskaya, "Hierarchical multi-label prediction of gene function," Bioinformatics, vol. 22, pp. 830-836, 2006.
    • (2006) Bioinformatics , vol.22 , pp. 830-836
    • Barutcuoglu, Z.1    Troyanskaya, O.2
  • 22
    • 0028312573 scopus 로고
    • A signal-dependent time-frequency representation: Fast algorithm for optimal kernel design
    • R. Baraniuk and D. Jones, "A signal-dependent time-frequency representation: Fast algorithm for optimal kernel design," IEEE Transactions on Signal Processing, vol. 42, no. 1, pp. 134-146, 1994.
    • (1994) IEEE Transactions on Signal Processing , vol.42 , Issue.1 , pp. 134-146
    • Baraniuk, R.1    Jones, D.2
  • 28
    • 84876811202 scopus 로고    scopus 로고
    • RCV1: A new benchmark collection for text categorization research
    • D. Lewis, Y. Yang, T. Rose, and F. Li, "RCV1: A new benchmark collection for text categorization research," Journal of Machine Learning Research, vol. 5, pp. 361-397, 2004.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 361-397
    • Lewis, D.1    Yang, Y.2    Rose, T.3    Li, F.4
  • 32
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
    • MIT Press
    • J. C. Platt, "Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods," in Advances in Large Margin Classifiers. MIT Press, 1999, pp. 61-74.
    • (1999) Advances in Large Margin Classifiers , pp. 61-74
    • Platt, J.C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.