Evidence optimization for consequently generated models
暂无分享,去创建一个
[1] N. Draper,et al. Applied Regression Analysis. , 1967 .
[2] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[3] A. P. Dawid,et al. Generative or Discriminative? Getting the Best of Both Worlds , 2007 .
[4] R. Stolzenberg,et al. Multiple Regression Analysis , 2004 .
[5] C. L. Mallows. Some comments on C_p , 1973 .
[6] John H. Maindonald,et al. Modern Multivariate Statistical Techniques: Regression, Classification and Manifold Learning , 2009 .
[7] Dick den Hertog,et al. Order of Nonlinearity as a Complexity Measure for Models Generated by Symbolic Regression via Pareto Genetic Programming , 2009, IEEE Transactions on Evolutionary Computation.
[8] A. McQuarrie,et al. Regression and Time Series Model Selection , 1998 .
[9] David A. Belsley,et al. Conditioning Diagnostics: Collinearity and Weak Data in Regression , 1991 .
[10] Ilkay Ulusoy,et al. Generative versus discriminative methods for object recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[11] Shang-Liang Chen,et al. Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.
[12] Ian T. Jolliffe,et al. Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.
[13] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[14] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[15] L. Hogben. Handbook of Linear Algebra , 2006 .
[16] Ian T. Nabney,et al. Netlab: Algorithms for Pattern Recognition , 2002 .
[17] J. Hull. Options, Futures, and Other Derivatives , 1989 .
[18] Noelle Foreshaw. Options… , 2010 .
[19] C. Mallows. Some Comments on Cp , 2000, Technometrics.
[20] Christopher M. Bishop,et al. A New Framework for Machine Learning , 2008, WCCI.
[21] R. Tibshirani,et al. Least angle regression , 2004, math/0406456.
[22] Laverne W. Stanton,et al. Applied Regression Analysis: A Research Tool , 1990 .
[23] David R. Anderson,et al. Model Selection and Multimodel Inference , 2003 .
[24] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .
[25] Donald W. Marquaridt. Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation , 1970 .
[26] M. Fireman,et al. MULTIPLE REGRESSION ANALYSIS OF SOIL DATA , 1954 .
[27] Sheng Chen,et al. Orthogonal least squares methods and their application to non-linear system identification , 1989 .
[28] I. Zelinka,et al. ANALYTIC PROGRAMMING – SYMBOLIC REGRESSION BY MEANS OF ARBITRARY EVOLUTIONARY ALGORITHMS , 2005 .