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Volumn 5, Issue , 2009, Pages 49-56

A new perspective for information theoretic feature selection

Author keywords

[No Author keywords available]

Indexed keywords

CLASS LABELS; CONTINUOUS SPACES; FILTER CRITERIA; MUTUAL INFORMATIONS; STATISTICAL CRITERION;

EID: 83455217064     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (138)

References (13)
  • 1
    • 0028468293 scopus 로고
    • Using mutual information for selecting features in supervised neural net learning
    • Battiti, R. (1994). Using mutual information for selecting features in supervised neural net learning. IEEE Trans. Neural Networks, 5(4):537-550.
    • (1994) IEEE Trans. Neural Networks , vol.5 , Issue.4 , pp. 537-550
    • Battiti, R.1
  • 2
    • 0011411948 scopus 로고
    • On the applications of mobius inversion in combinatorial analysis
    • Bender, E. A. and Goldman, J. R. (1975). On the Applications of Mobius Inversion in Combinatorial Analysis. Amer. Math. Monthly, 82:789-803.
    • (1975) Amer. Math. Monthly , vol.82 , pp. 789-803
    • Bender, E.A.1    Goldman, J.R.2
  • 4
    • 33645690579 scopus 로고    scopus 로고
    • Fast binary feature selection with conditional mutual information
    • Fleuret, F. (2004). Fast Binary Feature Selection with Conditional Mutual Information. The Journal of Machine Learning Research, 5:1531-1555.
    • (2004) The Journal of Machine Learning Research , vol.5 , pp. 1531-1555
    • Fleuret, F.1
  • 5
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Guyon, I. and Elisseeff, A. (2003). An introduction to variable and feature selection. Journal of Machine Learning Research, 3(7-8):1157-1182.
    • (2003) Journal of Machine Learning Research , vol.3 , Issue.7-8 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 6
    • 0036127473 scopus 로고    scopus 로고
    • Input feature selection for classification problems
    • Kwak, N. and Choi, C. (2002). Input Feature Selection for Classification Problems. Neural Networks, IEEE Transactions on, 13(1):143-159.
    • (2002) Neural Networks, IEEE Transactions on , vol.13 , Issue.1 , pp. 143-159
    • Kwak, N.1    Choi, C.2
  • 7
    • 34948823930 scopus 로고    scopus 로고
    • Conditional infomax learning: An integrated framework for feature extraction and fusion
    • Lin, D. and Tang, X. (2006). Conditional Infomax Learning: An Integrated Framework for Feature Extraction and Fusion. In European Conference on Computer Vision.
    • (2006) European Conference on Computer Vision
    • Lin, D.1    Tang, X.2
  • 8
    • 84937351341 scopus 로고
    • Multivariate information transmission
    • McGill, W. (1954). Multivariate information transmission. IEEE Trans. Inf. Theory, 4(4):93-111.
    • (1954) IEEE Trans. Inf. Theory , vol.4 , Issue.4 , pp. 93-111
    • McGill, W.1
  • 9
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and minredundancy
    • Peng, H., Long, F., and Ding, C. (2005). Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and MinRedundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8):1226-1238.
    • (2005) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.27 , Issue.8 , pp. 1226-1238
    • Peng, H.1    Long, F.2    Ding, C.3
  • 10
    • 34347166234 scopus 로고
    • On the foundations of combinatorial theory I. Theory of mobius functions
    • Rota, G. (1964). On the Foundations of Combinatorial Theory I. Theory of Mobius Functions. Probability Theory and Related Fields, 2:340-368.
    • (1964) Probability Theory and Related Fields , vol.2 , pp. 340-368
    • Rota, G.1
  • 11
    • 84856043672 scopus 로고
    • A mathematical theory of communication
    • Shannon, C. (1948). A mathematical theory of communication, Bell Syst. Tech. J, 27(3):379-423.
    • (1948) Bell Syst. Tech. J , vol.27 , Issue.3 , pp. 379-423
    • Shannon, C.1
  • 13
    • 0242484358 scopus 로고    scopus 로고
    • Data visualization and feature selection: New algorithms for nongaussian data
    • Yang, H. and Moody, J. (1999). Data Visualization and Feature Selection: New Algorithms for Nongaussian Data. Advances in Neural Information Processing Systems, 12.
    • (1999) Advances in Neural Information Processing Systems , vol.12
    • Yang, H.1    Moody, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.