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Nonlinear logistic discrimination via regularized radial basis functions for classifying high-dimensional data

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  • Tomohiro Ando
  • Sadanori Konishi

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  • Tomohiro Ando & Sadanori Konishi, 2009. "Nonlinear logistic discrimination via regularized radial basis functions for classifying high-dimensional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(2), pages 331-353, June.
    • Handle: RePEc:spr:aistmt:v:61:y:2009:i:2:p:331-353
    DOI: 10.1007/s10463-007-0143-3
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    References listed on IDEAS

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    1. Yoshisuke Nonaka & Sadanori Konishi, 2005. "Nonlinear regression modeling using regularized local likelihood method," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(4), pages 617-635, December.
    2. Sadanori Konishi, 2004. "Bayesian information criteria and smoothing parameter selection in radial basis function networks," Biometrika, Biometrika Trust, vol. 91(1), pages 27-43, March.
    3. Dudoit S. & Fridlyand J. & Speed T. P, 2002. "Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 77-87, March.
    4. Seiya Imoto & Sadanori Konishi, 2003. "Selection of smoothing parameters inB-spline nonparametric regression models using information criteria," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(4), pages 671-687, December.
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