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Volumn , Issue , 2010, Pages 315-322

Multilabel classification with meta-level features

Author keywords

Comparative evaluation; Learning to rank; Model design; Multi label classification

Indexed keywords

ALTERNATIVE APPROACH; BENCHMARK DATASETS; COMPARATIVE EVALUATIONS; CONTROLLED EXPERIMENT; EFFECTIVE LEARNING; EMPIRICAL EVIDENCE; FEATURE SPACE; HIGH DIMENSIONAL SPACES; LEARNING TO RANK; LEVEL OF ABSTRACTION; LOGISTIC REGRESSIONS; MODEL COMPLEXITY; MODEL DESIGN; MULTI-LABEL CLASSIFICATIONS; RETRIEVAL ALGORITHMS; STATE-OF-THE-ART METHODS;

EID: 77956045017     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1835449.1835503     Document Type: Conference Paper
Times cited : (109)

References (25)
  • 3
    • 68949141664 scopus 로고    scopus 로고
    • Combining instance-based learning and logistic regression for multilabel classification
    • W. Cheng and E. Hüllermeier. Combining Instance-Based Learning and Logistic Regression for Multilabel Classification. Journal of Machine Learning Research 2009, pages 211-255.
    • (2009) Journal of Machine Learning Research , pp. 211-255
    • Cheng, W.1    Hüllermeier, E.2
  • 4
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons for classifiers over multiple data sets
    • J. Demsar. Statistical comparisons for classifiers over multiple data sets. Journal of Machine Learning Research 2006, pages 1-30.
    • (2006) Journal of Machine Learning Research , pp. 1-30
    • Demsar, J.1
  • 6
    • 58149287952 scopus 로고    scopus 로고
    • An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons
    • S. Garcia and F. Herrera. An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons. Journal of Machine Learning Research 2008, pages 2677-2694.
    • (2008) Journal of Machine Learning Research , pp. 2677-2694
    • Garcia, S.1    Herrera, F.2
  • 8
    • 31844446804 scopus 로고    scopus 로고
    • A support vector method for multivariate performance measures
    • T. Joachims: A support vector method for multivariate performance measures. International Conference on Machine Learning 2005, pages 377-384.
    • (2005) International Conference on Machine Learning , pp. 377-384
    • Joachims, T.1
  • 11
    • 1942516915 scopus 로고    scopus 로고
    • A loss function analysis for classification methods in text categorization
    • F. Li and Y. Yang. A loss function analysis for classification methods in text categorization. International Conference on Machine Learning 2003, pages 472-479.
    • International Conference on Machine Learning 2003 , pp. 472-479
    • Li, F.1    Yang, Y.2
  • 14
  • 15
    • 0033281701 scopus 로고    scopus 로고
    • Improved boosting algorithms using confidence-rated predictions
    • R.E. Schapire and Y. Singer. Improved boosting algorithms using confidence-rated predictions. Journal of Machine learning Research 1999, pages 297-336.
    • (1999) Journal of Machine Learning Research , pp. 297-336
    • Schapire, R.E.1    Singer, Y.2
  • 19
    • 36448954244 scopus 로고    scopus 로고
    • AdaRank: A boosting algorithm for information retrieval
    • Jun Xu and Hang Li. AdaRank: a boosting algorithm for information retrieval. ACM SIGIR 2007, pages 391-398.
    • ACM SIGIR 2007 , pp. 391-398
    • Xu, J.1    Li, H.2
  • 20
    • 84984720462 scopus 로고    scopus 로고
    • Expert network: Effective and efficient learning from human decisions in text categorization and retrieval
    • Y. Yang: Expert Network: Effective and Efficient Learning from Human Decisions in Text Categorization and Retrieval. ACM SIGIR 1994, pages 13-22.
    • ACM SIGIR 1994 , pp. 13-22
    • Yang, Y.1
  • 21
    • 0034785186 scopus 로고    scopus 로고
    • A study of thresholding strategies for text categorization
    • Y. Yang. A Study of thresholding strategies for text categorization. ACM SIGIR 2001, pages 137-145.
    • ACM SIGIR 2001 , pp. 137-145
    • Yang, Y.1
  • 22
    • 27144441097 scopus 로고    scopus 로고
    • An evaluation of statistical approaches for text classification
    • Y. Yang. An evaluation of statistical approaches for text classification. Information Retrieval 1999. Vol 1, No. 1/2, pages 67-88.
    • Information Retrieval 1999 , vol.1 , Issue.1-2 , pp. 67-88
    • Yang, Y.1
  • 25
    • 33947681316 scopus 로고    scopus 로고
    • ML-kNN: A lazy learning approach to multi-label learning
    • ML Zhang and ZH Zhou. ML-kNN: A lazy learning approach to multi-label learning. Pattern Recognition 2007, pages 2038-2048.
    • Pattern Recognition 2007 , pp. 2038-2048
    • Zhang, M.L.1    Zhou, Z.H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.