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Volumn , Issue , 2011, Pages 17-24

Multi-label classification on tree- and DAG-structured hierarchies

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ALGORITHM; CLASSIFIER TRAINING; COMPUTATIONALLY EFFICIENT; DATA SETS; DIRECTED ACYCLIC GRAPHS; FUNCTIONAL GENOMICS; GREEDY STRATEGIES; MULTI-LABEL; OPTIMALITY; REAL-WORLD APPLICATION; RESEARCH EFFORTS; STATE-OF-THE-ART METHODS; SUBGRAPHS; THEORETICAL RESULT; TRAINING DATA;

EID: 80053440655     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (172)

References (17)
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  • 4
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  • 5
    • 77949529159 scopus 로고    scopus 로고
    • Decision trees for hierarchical multilabel classification: A case study in functional genomics
    • Berlin, Germany
    • Blockeel, H., Schietgat, L., Struyf, J., Dzeroski, S., and Clare, A. Decision trees for hierarchical multilabel classification: A case study in functional genomics. In PKDD, Berlin, Germany, 2006.
    • (2006) PKDD
    • Blockeel, H.1    Schietgat, L.2    Struyf, J.3    Dzeroski, S.4    Clare, A.5
  • 8
    • 77956528679 scopus 로고    scopus 로고
    • Multi-label prediction via compressed sensing
    • MIT Press
    • Hsu, D., Kakade, S.M., Langford, J., and Zhang, T. Multi-label prediction via compressed sensing. In NIPS 22, pp. 772-780. MIT Press, 2009.
    • (2009) NIPS 22 , pp. 772-780
    • Hsu, D.1    Kakade, S.M.2    Langford, J.3    Zhang, T.4
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    • Multi-label literature classification based on the gene ontology graph
    • Jin, B., Muller, B., Zhai, C., and Lu, X. Multi-label literature classification based on the gene ontology graph. BMC Bioinformatics, 9, 2008.
    • (2008) BMC Bioinformatics , pp. 9
    • Jin, B.1    Muller, B.2    Zhai, C.3    Lu, X.4
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    • A survey of hierarchical classification across different application domains
    • Silla, C.N. and Freitas, A.A. A survey of hierarchical classification across different application domains. Data Mining and Knowledge Discovery, 22(1-2):31-72, 2010.
    • (2010) Data Mining and Knowledge Discovery , vol.22 , Issue.1-2 , pp. 31-72
    • Silla, C.N.1    Freitas, A.A.2
  • 17
    • 33947681316 scopus 로고    scopus 로고
    • ML-KNN: A lazy learning approach to multi-label learning
    • Zhang, M.-L. and Zhou, Z.-H. ML-KNN: A lazy learning approach to multi-label learning. Pattern Recognition, 40(7), 2007.
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    • Zhang, M.-L.1    Zhou, Z.-H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.