Modeling for Optimal Probability Prediction

Keywords

Computer science

References

• Ideal spacial adaptation via wavelet shrinkageDavid L. Donoho — 1994
• An introduction to categorical data analysisAlan Agresti — 1997
• Some Comments on CpCohn L. Mallows — 2000
• On Information and SufficiencyHuaiyu Zhu — 1997
• Classical inference and the linear modelM. G. Kendall, Alan Stuart, J. K. Ord — 1999
• The risk inflation criterion for multiple regressionDean P. Foster, Edward I. George — 1994
• Nonparametric Maximum Likelihood Estimation of a Mixing DistributionNan M. Laird — 1978
• On characterization of the kullback-leibler mean information for continuous probability distributionsSadao Ikeda — 1962
• Some comments onL. C. Kwek, C. H. Oh — 1998
• Ridge Regression: Biased Estimation for Nonorthogonal ProblemsArthur E. Hoerl, Robert W. Kennard — 2000
• Modeling By Shortest Data Description*J. Rissanen — 1978
• Better subset regression using the nonnegative garroteLeo Breiman — 1995
• Estimation of a mixing distribution functionJ. R. Blum, V. Susarla — 1977
• More comments on C pColin L. Mallows — 1995
• The Empirical Bayes Approach to Statistical Decision ProblemsHerbert Robbins — 1964
• UCI Repository of machine learning databasesCatherine Blake — 1998
• Construction of Sequences Estimating the Mixing DistributionJohn Deely, Robert L. Kruse — 1968
• C4.5: Programs for Machine LearningJ. R. Quinlan — 1992
• Regression Shrinkage and Selection via the LassoRobert Tibshirani — 1996
• Estimating the Dimension of a ModelGideon Schwarz — 1978

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