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Volumn 2, Issue , 2008, Pages 758-763

Constraint projections for ensemble learning

Author keywords

[No Author keywords available]

Indexed keywords

TREES (MATHEMATICS);

EID: 57749179481     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (40)

References (16)
  • 3
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    • Bagging predictors
    • Breiman, L. 1996. Bagging predictors. Machine Learning 24(2):123-140.
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    • Breiman, L.1
  • 4
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman, L. 2001. Random forests. Machine Learning 45(1):5-32.
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 5
    • 57749181044 scopus 로고    scopus 로고
    • Davidson, I., and Basu, S. 2007. A survey of clustering with instance level constraints. [http://www. cs.ucdavis.edu/̃davidson/constrained- clustering/CARE-ER/Survey. pdf], constrained-clustering.org.
    • Davidson, I., and Basu, S. 2007. A survey of clustering with instance level constraints. [http://www. cs.ucdavis.edu/̃davidson/constrained- clustering/CARE-ER/Survey. pdf], constrained-clustering.org.
  • 6
    • 0002978642 scopus 로고    scopus 로고
    • Experiments with a new boosting algorithm
    • Freund, Y., and Schapire, R. 1996. Experiments with a new boosting algorithm. In ICML, 148-156.
    • (1996) ICML , pp. 148-156
    • Freund, Y.1    Schapire, R.2
  • 8
    • 0032139235 scopus 로고    scopus 로고
    • The random subspace method for constructing decision forests
    • Ho, T. 1998. The random subspace method for constructing decision forests. IEEE Trans. Pattern Analysis and Machine Intelligence 20(8):832-844.
    • (1998) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.20 , Issue.8 , pp. 832-844
    • Ho, T.1
  • 10
    • 36849031309 scopus 로고    scopus 로고
    • Liu, Y.; Jin, R.; and Jain, A. 2007. Boostcluster: Boosting clustering by pairwise constraints. In KDD, 450-459. Opitz, D. 1999. Feature selection for ensembles. In AAAI, 379-384.
    • Liu, Y.; Jin, R.; and Jain, A. 2007. Boostcluster: Boosting clustering by pairwise constraints. In KDD, 450-459. Opitz, D. 1999. Feature selection for ensembles. In AAAI, 379-384.
  • 12
    • 36849025479 scopus 로고    scopus 로고
    • Enhancing semi-supervised clustering: A feature projection perspective
    • Tang, W.; Xiong, H.; Zhong, S.; and Wu, J. 2007. Enhancing semi-supervised clustering: A feature projection perspective. In KDD, 707-716.
    • (2007) KDD , pp. 707-716
    • Tang, W.1    Xiong, H.2    Zhong, S.3    Wu, J.4
  • 13
    • 33744962383 scopus 로고    scopus 로고
    • Random sampling for subspace face recognition
    • Wang, X., and Tang, X. 2006. Random sampling for subspace face recognition. International Journal Computer Vision 70(1):91-104.
    • (2006) International Journal Computer Vision , vol.70 , Issue.1 , pp. 91-104
    • Wang, X.1    Tang, X.2
  • 15
    • 57749197763 scopus 로고    scopus 로고
    • Semi-supervised dimensionality reduction
    • Zhang, D.; Zhou, Z.-H.; and Chen, S. 2007. Semi-supervised dimensionality reduction. In SDM, 629-634.
    • (2007) SDM , pp. 629-634
    • Zhang, D.1    Zhou, Z.-H.2    Chen, S.3
  • 16
    • 24644441048 scopus 로고    scopus 로고
    • Ensembling local learners through multimodal perturbation
    • Zhou, Z.-H., and Yu, Y. 2005. Ensembling local learners through multimodal perturbation. IEEE Trans. System, Man and Cybernetics-Part B 35(4):725-735.
    • (2005) IEEE Trans. System, Man and Cybernetics-Part B , vol.35 , Issue.4 , pp. 725-735
    • Zhou, Z.-H.1    Yu, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.