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Volumn 16, Issue 2, 2006, Pages 569-588

Estimation of generalization error: Random and fixed inputs

Author keywords

Averaging; Logistic; Margins; Penalization; Support vector

Indexed keywords


EID: 33746128910     PISSN: 10170405     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (17)

References (18)
  • 1
    • 0003408496 scopus 로고    scopus 로고
    • University of California, Irvine, Department of Information and Computer Science
    • Blake, C. L. and Merz, C. J. (1998). UCI Repository of machine learning databases. http://www.ics.uci.edu/mlearn/MLRepository.html. University of California, Irvine, Department of Information and Computer Science.
    • (1998) UCI Repository of Machine Learning Databases
    • Blake, C.L.1    Merz, C.J.2
  • 2
    • 0033721433 scopus 로고    scopus 로고
    • Massive data discrimination via linear support vector machines
    • Bradley, P. S. and Mangasarian, O. L. (2000). Massive data discrimination via linear support vector machines. Optimization Methods and Software 13, 1-10.
    • (2000) Optimization Methods and Software , vol.13 , pp. 1-10
    • Bradley, P.S.1    Mangasarian, O.L.2
  • 3
    • 0001587464 scopus 로고
    • The little bootstrap and other methods for dimensionality selection in regression: X-fixed prediction error
    • Breiman, L. (1992). The little bootstrap and other methods for dimensionality selection in regression: X-fixed prediction error. J. Amer. Statist. Assoc. 87, 738-754.
    • (1992) J. Amer. Statist. Assoc. , vol.87 , pp. 738-754
    • Breiman, L.1
  • 4
    • 0000343716 scopus 로고
    • Submodel selection and evaluation in regression - The X - Random case
    • Breiman, L. and Spector, P. (1992). Submodel selection and evaluation in regression - the X - Random case. Internat. Rev. Statist. 3, 291-319.
    • (1992) Internat. Rev. Statist. , vol.3 , pp. 291-319
    • Breiman, L.1    Spector, P.2
  • 5
    • 0030344230 scopus 로고    scopus 로고
    • Heuristics of instability and stabilization in model selection
    • Breiman, L. (1996). Heuristics of instability and stabilization in model selection. Ann. Statist. 24, 2350-2383.
    • (1996) Ann. Statist. , vol.24 , pp. 2350-2383
    • Breiman, L.1
  • 6
    • 34249753618 scopus 로고
    • Support vector networks
    • Cortes, C. and Vapnik, V. (1995). Support vector networks. Machine Learning 20, 273-297.
    • (1995) Machine Learning , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 8
    • 85012466035 scopus 로고    scopus 로고
    • Discussion of Efron's paper entitled "The estimation of prediction error: Covariance penalties and Cross-Validation"
    • Denby, L., Landwehr, J. M. and Mallows, C. L. (2004). Discussion of Efron's paper entitled "The estimation of prediction error: covariance penalties and Cross-Validation". J. Amer. Statist. Assoc. 90, 633-634.
    • (2004) J. Amer. Statist. Assoc. , vol.90 , pp. 633-634
    • Denby, L.1    Landwehr, J.M.2    Mallows, C.L.3
  • 9
    • 84950461478 scopus 로고
    • Estimating the error rate of a prediction rule: Improvement on cross-validation
    • Efron, B. (1983). Estimating the error rate of a prediction rule: improvement on cross-validation. J. Amer. Statist. Assoc. 78, 316-331.
    • (1983) J. Amer. Statist. Assoc. , vol.78 , pp. 316-331
    • Efron, B.1
  • 10
    • 80053264999 scopus 로고
    • How biased is the apparent error rate of a prediction rule?
    • Efron, B. (1986). How biased is the apparent error rate of a prediction rule?. J. Amer. Statist. Assoc. 81, 461-470.
    • (1986) J. Amer. Statist. Assoc. , vol.81 , pp. 461-470
    • Efron, B.1
  • 11
    • 4944239996 scopus 로고    scopus 로고
    • The estimation of prediction error: Covariance penalties and cross-validation
    • Efron, B. (2004). The estimation of prediction error: covariance penalties and cross-validation. J. Amer. Statist. Assoc. 99, 619-632.
    • (2004) J. Amer. Statist. Assoc. , vol.99 , pp. 619-632
    • Efron, B.1
  • 13
    • 2142775432 scopus 로고    scopus 로고
    • Multicategory support vector machines, theory and application to the classification of microarray data and satellite radiance data
    • Lee, Y., Lin, Y. and Wahba, G. (2003). Multicategory support vector machines, theory and application to the classification of microarray data and satellite radiance data. J. Amer. Statist. Assoc. 99, 67-81.
    • (2003) J. Amer. Statist. Assoc. , vol.99 , pp. 67-81
    • Lee, Y.1    Lin, Y.2    Wahba, G.3
  • 14
    • 0001462696 scopus 로고
    • L, cross-validation and generalized cross-validation: Discrete index set
    • L, cross-validation and generalized cross-validation: Discrete index set. Ann. Statist. 15, 958-975.
    • (1987) Ann. Statist. , vol.15 , pp. 958-975
    • Li, K.C.1
  • 15
    • 33745635949 scopus 로고    scopus 로고
    • Optimal model assessment, selection and combination
    • to appear
    • Shen, X. and Huang, H.-C. (2005). Optimal model assessment, selection and combination. J. Amer. Statist. Assoc., to appear.
    • (2005) J. Amer. Statist. Assoc.
    • Shen, X.1    Huang, H.-C.2
  • 16
    • 4544352662 scopus 로고    scopus 로고
    • Adaptive model selection and assessment for exponential family distributions
    • Shen, X., Huang, H.-C. and Ye, J. (2004). Adaptive model selection and assessment for exponential family distributions. Technometrics 46, 306-317.
    • (2004) Technometrics , vol.46 , pp. 306-317
    • Shen, X.1    Huang, H.-C.2    Ye, J.3
  • 18
    • 0000864140 scopus 로고
    • The necessary and sufficient conditions for consistency of the method of empirical risk minimization
    • Vapnik, V. and Chervonenkis, A. (1991). The necessary and sufficient conditions for consistency of the method of empirical risk minimization. Pattern Recogn. Image Anal. 1, 284-305.
    • (1991) Pattern Recogn. Image Anal. , vol.1 , pp. 284-305
    • Vapnik, V.1    Chervonenkis, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.