메뉴 건너뛰기




Volumn , Issue , 2005, Pages 319-324

Feature selection in the prediction of infliximab dose increase

Author keywords

Feature selection; Real life data; Recursive feature elimination; Rheumatoid arthritis; Support vector machine; TNF blockers

Indexed keywords

BIOLOGICAL THERAPIES; CHRONIC INFLAMMATORY; CLASSIFICATION PERFORMANCE; CLINICAL KNOWLEDGE; DOMAIN KNOWLEDGE; REAL LIFE DATA; RECURSIVE FEATURE ELIMINATION; RHEUMATOID ARTHRITIS;

EID: 84887261382     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (13)
  • 4
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • I. Guyon, J. Weston, S. Barnhill, V. Vapnik, Gene selection for cancer classification using support vector machines. Machine Learning, 46(1-3):389-422,2002
    • (2002) Machine Learning , vol.46 , Issue.1-3 , pp. 389-422
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 5
    • 0026877917 scopus 로고
    • The MOS 36-item short-form health survey (SF-36), I. Conceptual framework and item selection
    • J.E. Ware Jr., & C.D. Sherbourne, The MOS 36-item short-form health survey (SF-36), I. Conceptual framework and item selection, Med Care, 30, 1992, 473-483.
    • (1992) Med Care , vol.30 , pp. 473-483
    • Ware Jr., J.E.1    Sherbourne, C.D.2
  • 7
    • 34249753618 scopus 로고
    • Support-vector networks
    • C. Cortes, & V. Vapnik, Support-vector networks, Machine Learning, 20(3), 1995, 273-297.
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 8
    • 0000874557 scopus 로고
    • Theoretical foundations of the potential function method in pattern recognition learning
    • M. Aizerman, E. Braverman. & L. Rozonoer, Theoretical foundations of the potential function method in pattern recognition learning, Automation and Remote Control, 25, 1964, 821-837.
    • (1964) Automation and Remote Control , vol.25 , pp. 821-837
    • Aizerman, M.1    Braverman, E.2    Rozonoer, L.3
  • 9
    • 0037822222 scopus 로고    scopus 로고
    • Asymptotic behaviors of support vector machines with Gaussian kernel
    • S.S. Keerthi, & C.-J. Lin, Asymptotic behaviors of support vector machines with Gaussian kernel, Neural Computation, 15, 2003, 1667-1689.
    • (2003) Neural Computation , vol.15 , pp. 1667-1689
    • Keerthi, S.S.1    Lin, C.-J.2
  • 10
    • 0003413187 scopus 로고    scopus 로고
    • Englewood Cliffs, NJ: Prentice-Hall
    • S. Haykin, Neural Networks a Comprehensive Foundation 2nd edition (Englewood Cliffs, NJ: Prentice-Hall, 1998).
    • (1998) nd Edition
    • Haykin, S.1
  • 11
    • 0003410791 scopus 로고    scopus 로고
    • New York, NJ: Springer-Verlag
    • T. Kohonen, Self-organizing Maps, 2nd edition (New York, NJ: Springer-Verlag, 1997).
    • (1997) nd Edition
    • Kohonen, T.1
  • 12
    • 84964114702 scopus 로고
    • Symposium: The need and the means of cross-validation. I. Problems and design of cross-validation
    • 1951
    • Mosier, C. I. (1951) Symposium: The need and the means of cross-validation. I. Problems and design of cross-validation, Education and Psychological Measurement, 11, 1951, 5-11.
    • (1951) Education and Psychological Measurement , vol.11 , pp. 5-11
    • Mosier, C.I.1
  • 13
    • 0023890867 scopus 로고
    • Measuring the accuracy of diagnostic systems
    • June
    • J. A. Swets. Measuring the accuracy of diagnostic systems. Science, 240(4857):1285-1293, June 1988.
    • (1988) Science , vol.240 , Issue.4857 , pp. 1285-1293
    • Swets, J.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.