메뉴 건너뛰기




Volumn 3, Issue , 2003, Pages 1229-1243

Dimensionality reduction via sparse support vector machines

Author keywords

Bootstrap Aggregation; Dimensionality Reduction; Model Visualization; Pattern Search; Regression; Support Vector Machines; Variable Selection

Indexed keywords

DIMENSIONALITY REDUCTION; MODEL VISUALIZATION; PATTERN SEARCH; REGRESSION; VARIABLE SELECTION;

EID: 1542365112     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (355)

References (32)
  • 1
    • 0002935122 scopus 로고    scopus 로고
    • Combining support vector and mathematical programming methods for classification
    • B. Schölkopf, C. Burges, and A. Smola, editors, Cambridge, MA, MIT Press
    • K. P. Bennett. Combining support vector and mathematical programming methods for classification. In B. Schölkopf, C. Burges, and A. Smola, editors, Advances in Kernel Methods - Support Vector Machines, pages 307-326, Cambridge, MA, 1999. MIT Press.
    • (1999) Advances in Kernel Methods - Support Vector Machines , pp. 307-326
    • Bennett, K.P.1
  • 2
    • 0005154520 scopus 로고    scopus 로고
    • Geometry in learning
    • C. Gorini, E. Hart, W. Meyer, and T. Phillips, editors, Washington, D.C.,. Mathematical Association of America
    • K. P. Bennett and E. J. Bredensteiner. Geometry in learning. In C. Gorini, E. Hart, W. Meyer, and T. Phillips, editors, Geometry at Work, Washington, D.C., 1997. Mathematical Association of America. www.rpi.edu/-bennek/geometry2.ps.
    • (1997) Geometry at Work
    • Bennett, K.P.1    Bredensteiner, E.J.2
  • 5
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • L. Breiman. Bagging predictors. Machine Learning, 24(2):123-140, 1996.
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 6
    • 0000275022 scopus 로고    scopus 로고
    • Prediction games and arcing algorithms
    • L. Breiman. Prediction games and arcing algorithms. Neural Computation, 11(7):1493-1517, 1999.
    • (1999) Neural Computation , vol.11 , Issue.7 , pp. 1493-1517
    • Breiman, L.1
  • 8
  • 10
    • 84871421483 scopus 로고
    • Derivative-free pattern search methods for multidisciplinary design problems
    • American Institute of Aeronautics and Astronautics, Reston, VA
    • J. Dennis and V. Torczon. Derivative-free pattern search methods for multidisciplinary design problems. In The Fifth AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pages 922-932, American Institute of Aeronautics and Astronautics, Reston, VA, 1994.
    • (1994) The Fifth AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization , pp. 922-932
    • Dennis, J.1    Torczon, V.2
  • 13
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • I. Guyon, J. Weston, S. Barnhill, and V. Vapnik. Gene selection for cancer classification using support vector machines. Machine Learning, 46:389-422, 2002.
    • (2002) Machine Learning , vol.46 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 15
    • 0003578708 scopus 로고    scopus 로고
    • ILOG. ILOG CPLEX Division, Incline Village, NV
    • ILOG. ILOG CPLEX 6.5 Reference Manual. ILOG CPLEX Division, Incline Village, NV, 1999.
    • (1999) ILOG CPLEX 6.5 Reference Manual
  • 17
    • 0022848955 scopus 로고
    • Feature selection and extraction
    • T. Y. Young and K.-S. Fu, editors Academic Press, New York
    • J. Kittler. Feature selection and extraction. In T. Y. Young and K.-S. Fu, editors, Handbook of Pattern Recognition and Image Processing. Academic Press, New York, 1986.
    • (1986) Handbook of Pattern Recognition and Image Processing
    • Kittler, J.1
  • 18
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • R. Kohavi and G. H. John. Wrappers for feature subset selection. Artificial Intelligence, 1997(1 - 2): 273 - 323, 1997.
    • (1997) Artificial Intelligence , vol.1997 , Issue.1 , pp. 273-323
    • Kohavi, R.1    John, G.H.2
  • 19
    • 33244468970 scopus 로고    scopus 로고
    • Comparison of classifier-specific feature selection algorithms
    • M. Kudo, P. Somol, P. Pudil, M. Shimbo, and J. Sklansky. Comparison of classifier-specific feature selection algorithms. In SSPR/SPR, pages 677-686, 2000.
    • (2000) SSPR/SPR , pp. 677-686
    • Kudo, M.1    Somol, P.2    Pudil, P.3    Shimbo, M.4    Sklansky, J.5
  • 24
    • 0004094721 scopus 로고    scopus 로고
    • Ph.D. thesis, Technische Universität Berlin
    • A. J. Smola. Learning with Kernels. Ph.D. thesis, Technische Universität Berlin, 1998.
    • (1998) Learning with Kernels
    • Smola, A.J.1
  • 32
    • 0001413186 scopus 로고    scopus 로고
    • Feature subset selection using a genetic algorithm
    • J. Koza et al., editor Stanford University, CA, USA,. Morgan Kaufmann
    • J. Yang and V. Honavar. Feature subset selection using a genetic algorithm. In J. Koza et al., editor, Genetic Programming 1997: Proceedings of the Second Annual Conference, page 380, Stanford University, CA, USA, 1997. Morgan Kaufmann.
    • (1997) Genetic Programming 1997: Proceedings of the Second Annual Conference , pp. 380
    • Yang, J.1    Honavar, V.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.