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Volumn 33, Issue 10, 2012, Pages 1426-1433

A semi-supervised feature ranking method with ensemble learning

Author keywords

Ensemble learning; Feature selection; Semi supervised learning

Indexed keywords

BENCHMARK DATA; ENSEMBLE LEARNING; FEATURE RANKING; IMPORTANCE MEASURE; LABELED AND UNLABELED DATA; SEMI-SUPERVISED; SEMI-SUPERVISED ALGORITHM; SEMI-SUPERVISED LEARNING; UNLABELED DATA;

EID: 84860387759     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2012.03.001     Document Type: Article
Times cited : (43)

References (25)
  • 3
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • DOI 10.1023/A:1010933404324
    • L. Breiman Random forests Mach. Learn. 45 1 2001 5 32 (Pubitemid 32933532)
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 4
    • 84937549955 scopus 로고
    • The scree test for the number of factors
    • R.B. Cattell The scree test for the number of factors Multivar. Behav. Res. 2 1966 245 276
    • (1966) Multivar. Behav. Res. , vol.2 , pp. 245-276
    • Cattell, R.B.1
  • 6
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • J. Demsar Statistical comparisons of classifiers over multiple data sets J. Mach. Learn. Res. 7 2006 1 30 (Pubitemid 43022939)
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1-30
    • Demsar, J.1
  • 7
    • 26444454606 scopus 로고    scopus 로고
    • Feature selection for unsupervised learning
    • J. Dy, and C. Brodley Feature selection for unsupervised learning J. Mach. Learn. Res. 5 2004 845 889
    • (2004) J. Mach. Learn. Res. , vol.5 , pp. 845-889
    • Dy, J.1    Brodley, C.2
  • 9
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • I. Guyon, and A. Elisseeff An introduction to variable and feature selection J. Mach. Learn. Res. 3 2003 1157 1182
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 10
    • 78650296072 scopus 로고    scopus 로고
    • Combining committee-based semi-supervised learning and active learning
    • M.F.A. Hady, and F. Schwenker Combining committee-based semi-supervised learning and active learning J. Comput. Sci. Tech. 25 4 2010 681 698
    • (2010) J. Comput. Sci. Tech. , vol.25 , Issue.4 , pp. 681-698
    • Hady, M.F.A.1    Schwenker, F.2
  • 11
    • 44649105615 scopus 로고    scopus 로고
    • Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm
    • Y. Hong, S. Kwong, Y. Chang, and R. Qingsheng Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm Pattern Recognit. 41 9 2008 2742 2756
    • (2008) Pattern Recognit. , vol.41 , Issue.9 , pp. 2742-2756
    • Hong, Y.1    Kwong, S.2    Chang, Y.3    Qingsheng, R.4
  • 12
    • 38749139222 scopus 로고    scopus 로고
    • Consensus unsupervised feature randking from multiple views
    • Y. Hong, S. Kwong, Y. Chang, and Q. Ren Consensus unsupervised feature randking from multiple views Pattern Recognition Lett. 29 5 2008 595 602
    • (2008) Pattern Recognition Lett. , vol.29 , Issue.5 , pp. 595-602
    • Hong, Y.1    Kwong, S.2    Chang, Y.3    Ren, Q.4
  • 13
    • 54549099006 scopus 로고    scopus 로고
    • Performance of feature-selection methods in the classification of high-dimension data
    • J. Hua, W. Tembe, and E. Dougherty Performance of feature-selection methods in the classification of high-dimension data Pattern Recognit. 42 2009 409 424
    • (2009) Pattern Recognit. , vol.42 , pp. 409-424
    • Hua, J.1    Tembe, W.2    Dougherty, E.3
  • 19
    • 35748932917 scopus 로고    scopus 로고
    • A review of feature selection techniques in bioinformatics
    • Y. Saeys, I. Inza, and P. Larrañaga A review of feature selection techniques in bioinformatics Bioinformatics 23 2007 95 116
    • (2007) Bioinformatics , vol.23 , pp. 95-116
    • Saeys, Y.1    Inza, I.2    Larrañaga, P.3
  • 20
    • 33746424489 scopus 로고    scopus 로고
    • Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval
    • D. Tao, X. Tang, X. Li, and X. Wu Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval IEEE Trans. Pattern Anal. Machine Intell. 28 7 2006 1088 1099
    • (2006) IEEE Trans. Pattern Anal. Machine Intell. , vol.28 , Issue.7 , pp. 1088-1099
    • Tao, D.1    Tang, X.2    Li, X.3    Wu, X.4
  • 22
    • 77954565155 scopus 로고    scopus 로고
    • Discriminative semi-supervised feature selection via manifold regularization
    • Z. Xu, I. King, M.R. Lyu, and R. Jin Discriminative semi-supervised feature selection via manifold regularization IEEE Trans. Neural Networks 21 7 2010 1033 1047
    • (2010) IEEE Trans. Neural Networks , vol.21 , Issue.7 , pp. 1033-1047
    • Xu, Z.1    King, I.2    Lyu, M.R.3    Jin, R.4
  • 23
    • 77952554171 scopus 로고    scopus 로고
    • Co-training with relevant random subspaces
    • Y. Yaslan, and Z. Cataltepe Co-training with relevant random subspaces Neurocomputing 73 10-12 2010 1652 1661
    • (2010) Neurocomputing , vol.73 , Issue.1012 , pp. 1652-1661
    • Yaslan, Y.1    Cataltepe, Z.2
  • 24
    • 44649111202 scopus 로고    scopus 로고
    • Locality sensitive semi-supervised feature selection
    • J. Zhao, K. Lu, and X. He Locality sensitive semi-supervised feature selection Neurocomputing 71 10-12 2008 1842 1849
    • (2008) Neurocomputing , vol.71 , Issue.1012 , pp. 1842-1849
    • Zhao, J.1    Lu, K.2    He, X.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.