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Volumn , Issue , 2012, Pages 139-146

Hybrid binary-chain multi-label classifiers

Author keywords

[No Author keywords available]

Indexed keywords

BINARY RELEVANCES; CORRELATION MATRIX; DIFFERENT CLASS; HYBRID APPROACH; INDEPENDENT CLASSIFIERS; MULTI-LABEL; MULTI-LABEL CLASSIFICATIONS; PREDICTIVE PERFORMANCE; SINGLE COMPOUND; TIME COMPLEXITY;

EID: 84874707478     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4)

References (16)
  • 2
    • 35748943218 scopus 로고    scopus 로고
    • A discretization algorithm based on class-attribute contingency coefficient
    • T. Cheng-Jung, L. Chien-I, and Y. Wei-Pang. 2008. A discretization algorithm based on class-attribute contingency coefficient. Information Sciences, (178):714-731.
    • (2008) Information Sciences , vol.178 , pp. 714-731
    • Cheng-Jung, T.1    Chien-I, L.2    Wei-Pang, Y.3
  • 3
    • 84933530882 scopus 로고
    • Approximating discrete probability distributions with dependence trees
    • C. Chow and C. Liu. 1968. Approximating discrete probability distributions with dependence trees. Information Theory, IEEE Transactions on, 14(3):462-467.
    • (1968) Information Theory, IEEE Transactions on , vol.14 , Issue.3 , pp. 462-467
    • Chow, C.1    Liu, C.2
  • 8
    • 83155175374 scopus 로고    scopus 로고
    • Classifier chains for multi-label classification
    • 10.1007/sl0994-011-5256-5
    • J. Read, B. Pfahringer, G. Holmes, and E. Frank. 2011. Classifier chains for multi-label classification. Machine Learning, 85:333-359. 10.1007/sl0994-011-5256-5.
    • (2011) Machine Learning , vol.85 , pp. 333-359
    • Read, J.1    Pfahringer, B.2    Holmes, G.3    Frank, E.4
  • 9
    • 0028483915 scopus 로고
    • Finding MAPs for belief networks is NP-hard
    • S. E. Shimony. 1994. Finding MAPs for belief networks is NP-hard. Artificial Intelligence, 68(2):399-410.
    • (1994) Artificial Intelligence , vol.68 , Issue.2 , pp. 399-410
    • Shimony, S.E.1
  • 16
    • 33947681316 scopus 로고    scopus 로고
    • Ml-knn: A lazy learning approach to multi-label learning
    • M. Ling Zhang and Z. Hua Zhou. 2007. Ml-knn: A lazy learning approach to multi-label learning. Pattern Recognition, 40(7):2038-2048.
    • (2007) Pattern Recognition , vol.40 , Issue.7 , pp. 2038-2048
    • Ling Zhang, M.1    Hua Zhou, Z.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.