메뉴 건너뛰기




Volumn 26, Issue 5, 2014, Pages 1131-1143

Efficient semi-supervised feature selection: Constraint, relevance, and redundancy

Author keywords

constraints; redundancy; relevance; Semi supervised feature selection

Indexed keywords

COMPUTATIONAL METHODS; INFORMATION SYSTEMS;

EID: 84901006505     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2013.86     Document Type: Article
Times cited : (83)

References (43)
  • 1
    • 84866453901 scopus 로고    scopus 로고
    • (Data Mining and Knowledge Discovery Series). Boca Raton, FL, USA: Chapman and Hall-CRC
    • Z. Zhao and H. Liu, Spectral Feature Selection for Data Mining (Data Mining and Knowledge Discovery Series). Boca Raton, FL, USA: Chapman and Hall-CRC, 2012.
    • (2012) Spectral Feature Selection for Data Mining
    • Zhao, Z.1    Liu, H.2
  • 2
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic problems
    • Sept.
    • R. Fisher, "The use of multiple measurements in taxonomic problems," Ann. Eugen, vol. 7, no. 2, pp. 179-188, Sept. 1936.
    • (1936) Ann. Eugen , vol.7 , Issue.2 , pp. 179-188
    • Fisher, R.1
  • 4
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • DOI 10.1126/science.290.5500.2323
    • S. T. Roweis and L. K. Saul, "Nonlinear dimensionality reduction by local linear embedding," Science, vol. 290, no. 5500, pp. 2323-2326, Dec. 2000. (Pubitemid 32041578)
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 5
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear Component Analysis as a Kernel Eigenvalue Problem
    • B. Scholkopf, A. Smola, and K. R. Muller, "Nonlinear component analysis as a Kernel Eigenvalue problem," Neural Comput., vol. 10, no. 5, pp. 1299-1319, 1998. (Pubitemid 128463674)
    • (1998) Neural Computation , vol.10 , Issue.5 , pp. 1299-1319
    • Scholkopf, B.1    Smola, A.2    Muller, K.-R.3
  • 6
    • 13444286179 scopus 로고    scopus 로고
    • Locality preserving projections
    • X. He and P. Niyogi, "Locality preserving projections," in Proc. NIPS, 2004.
    • (2004) Proc. NIPS
    • He, X.1    Niyogi, P.2
  • 7
    • 84880203756 scopus 로고    scopus 로고
    • Laplacian eigenmaps and spectral techniques for embedding and clustering
    • M. Belkin and P. Niyogi, "Laplacian eigenmaps and spectral techniques for embedding and clustering," in Proc. NIPS, 2002.
    • (2002) Proc. NIPS
    • Belkin, M.1    Niyogi, P.2
  • 8
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Mar.
    • I. Guyon and A. Elisseeff, "An introduction to variable and feature selection," J. Mach. Learn. Res., vol. 3, pp. 1157-1182, Mar. 2003.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 9
    • 26444454606 scopus 로고    scopus 로고
    • Feature selection for unsupervised learning
    • Aug.
    • J. G. Dy and C. E. Brodley, "Feature selection for unsupervised learning," J. Mach. Learn. Res., vol. 5, pp. 845-889, Aug. 2004.
    • (2004) J. Mach. Learn. Res. , vol.5 , pp. 845-889
    • Dy, J.G.1    Brodley, C.E.2
  • 11
    • 0141990695 scopus 로고    scopus 로고
    • Theoretical and empirical analysis of relief and relieff
    • M. Robnik-Sikonja and I. Kononenko, "Theoretical and empirical analysis of relief and relieff," Mach. Learn., vol. 53, no. 1-2, pp. 23-69, 2003.
    • (2003) Mach. Learn. , vol.53 , Issue.1-2 , pp. 23-69
    • Robnik-Sikonja, M.1    Kononenko, I.2
  • 12
    • 25144492516 scopus 로고    scopus 로고
    • Efficient feature selection via analysis of relevance and redundancy
    • Oct.
    • L. Yu and H. Liu, "Efficient feature selection via analysis of relevance and redundancy," J. Mach. Learn. Res., vol. 5, pp. 1205-1224, Oct. 2004.
    • (2004) J. Mach. Learn. Res. , vol.5 , pp. 1205-1224
    • Yu, L.1    Liu, H.2
  • 13
    • 34547981441 scopus 로고    scopus 로고
    • Spectral feature selection for supervised and unsupervised learning
    • Corvallis, OR, USA
    • Z. Zhao and H. Liu, "Spectral feature selection for supervised and unsupervised learning," in Proc. 24th Int. Conf. Mach. Learn., Corvallis, OR, USA, 2007.
    • (2007) Proc. 24th Int. Conf. Mach. Learn.
    • Zhao, Z.1    Liu, H.2
  • 15
    • 84864039505 scopus 로고    scopus 로고
    • Laplacian score for feature selection
    • Vancouver, BC, Canada
    • X. He, D. Cai, and P. Niyogi, "Laplacian score for feature selection," in Proc. NIPS, Vancouver, BC, Canada, 2005.
    • (2005) Proc. NIPS
    • He, X.1    Cai, D.2    Niyogi, P.3
  • 16
    • 84862024860 scopus 로고    scopus 로고
    • Feature selection via dependence maximization
    • Jan.
    • L. Song, A. Smola, A. Gretton, J. Bedo, and K. Borgwardt, "Feature selection via dependence maximization," J. Mach. Learn. Res., vol. 13, no. 1, pp. 1393-1434, Jan. 2012.
    • (2012) J. Mach. Learn. Res. , vol.13 , Issue.1 , pp. 1393-1434
    • Song, L.1    Smola, A.2    Gretton, A.3    Bedo, J.4    Borgwardt, K.5
  • 17
    • 70449102559 scopus 로고    scopus 로고
    • Semi-supervised feature selection via spectral analysis
    • Tempe, AZ, USA
    • Z. Zhao and H. Liu, "Semi-supervised feature selection via spectral analysis," in Proc. SIAM Int. Conf. Data Mining, Tempe, AZ, USA, 2007, pp. 641-646.
    • (2007) Proc. SIAM Int. Conf. Data Mining , pp. 641-646
    • Zhao, Z.1    Liu, H.2
  • 18
    • 21844457672 scopus 로고    scopus 로고
    • Learning a mahalanobis metric from equivalence constraints
    • Jan.
    • A. Bar-Hillel, T. Hertz, N. Shental, and D. Weinshall, "Learning a Mahalanobis metric from equivalence constraints," J. Mach. Learn. Res., vol. 6, pp. 937-965, Jan. 2005.
    • (2005) J. Mach. Learn. Res. , vol.6 , pp. 937-965
    • Bar-Hillel, A.1    Hertz, T.2    Shental, N.3    Weinshall, D.4
  • 20
    • 38349093039 scopus 로고    scopus 로고
    • Constraint score: A new filter method for feature selection with pairwise constraints
    • D. Zhang, S. Chen, and Z. Zhou, "Constraint score: A new filter method for feature selection with pairwise constraints," Pattern Recognit., vol. 41, no. 5, pp. 1440-1451, 2008.
    • (2008) Pattern Recognit. , vol.41 , Issue.5 , pp. 1440-1451
    • Zhang, D.1    Chen, S.2    Zhou, Z.3
  • 21
    • 78751645408 scopus 로고    scopus 로고
    • Constraint scores for semi-supervised feature selection: A comparative study
    • M. Kalakech, P. Biela, L. Macaire, and D. Hamad, "Constraint scores for semi-supervised feature selection: A comparative study," Pattern Recognit. Lett., vol. 32, no. 5, pp. 656-665, 2011.
    • (2011) Pattern Recognit. Lett. , vol.32 , Issue.5 , pp. 656-665
    • Kalakech, M.1    Biela, P.2    MacAire, L.3    Hamad, D.4
  • 22
    • 80052407690 scopus 로고    scopus 로고
    • Constrained laplacian score for semi-supervised feature selection
    • Athens, Greece
    • K. Benabdeslem and M. Hindawi, "Constrained Laplacian score for semi-supervised feature selection," in Proc. ECML-PKDD, Athens, Greece, 2011, pp. 204-218.
    • (2011) Proc. ECML-PKDD , pp. 204-218
    • Benabdeslem, K.1    Hindawi, M.2
  • 23
    • 38049127336 scopus 로고    scopus 로고
    • Measuring constraintset utility for partitional clustering algorithms
    • I. Davidson, K. Wagstaff, and S. Basu, "Measuring constraintset utility for partitional clustering algorithms," in Proc. ECML/PKDD, 2006.
    • (2006) Proc. ECML/PKDD
    • Davidson, I.1    Wagstaff, K.2    Basu, S.3
  • 24
    • 80052500135 scopus 로고    scopus 로고
    • Constraint selection for semisupervised topological clustering
    • Athens, Greece
    • K. Allab and K. Benabdeslem, "Constraint selection for semisupervised topological clustering," in Proc. ECML-PKDD, Athens, Greece, 2011, pp. 28-43.
    • (2011) Proc. ECML-PKDD , pp. 28-43
    • Allab, K.1    Benabdeslem, K.2
  • 25
    • 85158826352 scopus 로고    scopus 로고
    • Efficient spectral feature selection with minimum redundancy
    • Z. Zhao, L. Wang, and H. Liu, "Efficient spectral feature selection with minimum redundancy," in Proc. AAAI, 2010.
    • (2010) Proc. AAAI
    • Zhao, Z.1    Wang, L.2    Liu, H.3
  • 26
    • 84960463485 scopus 로고    scopus 로고
    • Minimum redundancy feature selection from microarray gene expression data
    • C. Ding and H. C. Peng, "Minimum redundancy feature selection from microarray gene expression data," in Proc. IEEE CSB, 2003, pp. 523-528.
    • (2003) Proc. IEEE CSB , pp. 523-528
    • Ding, C.1    Peng, H.C.2
  • 27
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy
    • DOI 10.1109/TPAMI.2005.159
    • H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 8, pp. 1226-1238, Aug. 2005. (Pubitemid 41245053)
    • (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
  • 28
    • 77954875021 scopus 로고    scopus 로고
    • Comparison of redundancy and relevance measures for feature selection in tissue classification of CT images
    • Berlin, Germany
    • B. Auffarth, M. Lopez, and J. Cerquides, "Comparison of redundancy and relevance measures for feature selection in tissue classification of CT images," in Proc. 10th ICDM, Berlin, Germany, 2010, pp. 248-262.
    • (2010) Proc. 10th ICDM , pp. 248-262
    • Auffarth, B.1    Lopez, M.2    Cerquides, J.3
  • 29
    • 84890520049 scopus 로고    scopus 로고
    • Use the zero norm with linear models and kernel methods
    • Mar.
    • J. Weston, A. Elisseff, B. Schoelkopf, and M. Tipping, "Use the zero norm with linear models and kernel methods," J. Mach. Learn. Res., vol. 3, pp. 1439-1461, Mar. 2003.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1439-1461
    • Weston, J.1    Elisseff, A.2    Schoelkopf, B.3    Tipping, M.4
  • 30
    • 84873278481 scopus 로고    scopus 로고
    • On similarity preserving feature selection
    • Mar.
    • Z. Zhao, L. Wang, H. Liu, and J. Ye, "On similarity preserving feature selection," IEEE Trans. Knowl. Data Eng., vol. 25, no. 3, pp. 619-632, Mar. 2013.
    • (2013) IEEE Trans. Knowl. Data Eng. , vol.25 , Issue.3 , pp. 619-632
    • Zhao, Z.1    Wang, L.2    Liu, H.3    Ye, J.4
  • 31
    • 0003882879 scopus 로고    scopus 로고
    • Providence, RI, USA: American Mathematical SoCiety
    • F. Chung, Spectral Graph Theory. Providence, RI, USA: American Mathematical SoCiety, 1997.
    • (1997) Spectral Graph Theory
    • Chung, F.1
  • 32
    • 84857166060 scopus 로고    scopus 로고
    • Constraint selection based semi-supervised feature selection
    • Vancouver, BC, Canada
    • M. Hindawi, K. Allab, and K. Benabdeslem, "Constraint selection based semi-supervised feature selection," in Proc. IEEE ICDM, Vancouver, BC, Canada, 2011, pp. 1080-1085.
    • (2011) Proc. IEEE ICDM , pp. 1080-1085
    • Hindawi, M.1    Allab, K.2    Benabdeslem, K.3
  • 33
  • 34
    • 0001457509 scopus 로고
    • Some methods for classification and analysis of multivariate observations
    • Berkley, CA, USA
    • J. B. MacQueen, "Some methods for classification and analysis of multivariate observations," in Proc. 5th Symp. Math. Statist. Probab., Berkley, CA, USA, 1967, pp. 281-297.
    • (1967) Proc. 5th Symp. Math. Statist. Probab. , pp. 281-297
    • MacQueen, J.B.1
  • 35
    • 84944178665 scopus 로고
    • Hierarchical grouping to optimize an objective function
    • J. H. Ward, "Hierarchical grouping to optimize an objective function," J. Amer. Statist. AsSoC., vol. 58, no. 301, pp. 236-244, 1963.
    • (1963) J. Amer. Statist. AsSoC. , vol.58 , Issue.301 , pp. 236-244
    • Ward, J.H.1
  • 36
    • 0042341570 scopus 로고    scopus 로고
    • Clustering and its validation in a symbolic framework
    • M. Kalyani and M. Sushmita, "Clustering and its validation in a symbolic framework," Pattern Recognit. Lett., vol. 24, no. 14, pp. 2367-2376, 2003.
    • (2003) Pattern Recognit. Lett. , vol.24 , Issue.14 , pp. 2367-2376
    • Kalyani, M.1    Sushmita, M.2
  • 38
    • 85162319688 scopus 로고    scopus 로고
    • Sparse manifold clustering and embedding
    • E. Elhamifar and R. Vidal, "Sparse manifold clustering and embedding," in Proc. NIPS, 2011, pp. 55-63.
    • (2011) Proc. NIPS , pp. 55-63
    • Elhamifar, E.1    Vidal, R.2
  • 39
    • 0004257992 scopus 로고
    • (Wiley Series in Probability and Mathematical Statistics). New York, NY, USA: Wiley
    • S. Kullback, Information Theory and Statistics (Wiley Series in Probability and Mathematical Statistics). New York, NY, USA: Wiley, 1959.
    • (1959) Information Theory and Statistics
    • Kullback, S.1
  • 42
    • 79955702502 scopus 로고    scopus 로고
    • LIBSVM: A library for support vector machines
    • [Online]
    • C. C. Chang and C. J. Lin, "LIBSVM: A library for support vector machines," ACM Trans. Intell. Syst. Technol., vol. 2, pp. 27:1-27:27, 2011 [Online]. Available: http://www.csie.ntu.edu.tw/~cjlin/libsvm
    • (2011) ACM Trans. Intell. Syst. Technol. , vol.2 , pp. 1-27
    • Chang, C.C.1    Lin, C.J.2
  • 43
    • 84950632109 scopus 로고
    • Objective criteria for the evaluation of clustering method
    • Dec.
    • W. M. Rand, "Objective criteria for the evaluation of clustering method," J. Amer. Statist. AsSoC., vol. 66, no. 336, pp. 846-850, Dec. 1971.
    • (1971) J. Amer. Statist. AsSoC. , vol.66 , Issue.336 , pp. 846-850
    • Rand, W.M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.