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This paper continues study, both theoretical and empirical, of the method of Venn prediction, concentrating on binary prediction problems.
An empirical distribution function for sampling with incomplete information
Miriam Ayer, H. Daniel Brunk, George M. Ewing, W. T. Reid, and Edward Silverman · 1955
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Verification of probabilistic predictions: a brief review
Allan H. Murphy and Edward S. Epstein · 1967
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Statistical Inference under Order Restrictions: The Theory and Application of Isotonic Regression
Richard E. Barlow, D. J. Bartholomew, J. M. Bremner, and H. Daniel Brunk · 1972
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Theoretical Statistics
David R. Cox and David V. Hinkley · 1974
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Testing Statistical Hypotheses
Erich L. Lehmann · 1986
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Probabilities for SV machines
John C. Platt · 2000
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Transforming classifier scores into accurate multiclass probability estimates
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John Langford and Bianca Zadrozny · 2005
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Vladimir Vovk, Alex Gammerman, and Glenn Shafer · 2005
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A. Frank and A. Asuncion · 2010
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The WEKA data mining software: an update
Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten · 2011
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Smooth isotonic regression: a new method to calibrate predictive models
Xiaoqian Jiang, Melanie Osl, Jihoon Kim, and Lucila Ohno-Machado · 2011
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Reliable probability estimates based on support vector machines for large multiclass datasets
Antonis Lambrou, Harris Papadopoulos, Ilia Nouretdinov, and Alex Gammerman · 2012
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Alexandru Niculescu-Mizil and Rich Caruana · 2012
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R: A Language and Environment for Statistical Computing
R Core Team · 2014
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