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Abstract: : This paper first reviews the reasoning behind the Bayesian "evidence" procedure for setting parameters in the probability distributions involved in inductive inference. This paper then proves that the evidence procedure is incorrect. More precisely, this paper proves that the assumptions going into the evidence procedure do not, as claimed, "let the data determine the distributions ". Instead, those assumptions simply amount to an implicit replacement of the original distributions, containing ... (Update)
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BibTeX entry: (Update)
@techreport{ wolpert92rigorous,
author = "D. H. Wolpert",
title = "A rigorous investigation of `evidence' and `{O}ccam factors' in {B}ayesian reasoning'",
number = "T.R. 92-03-013",
year = "1992",
url = "citeseer.ist.psu.edu/298958.html" }
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96 Occam's razor (context) - Blumer - 1987
91 Bayesian back-propagation (context) - Buntine, Weigend - 1991
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58 Statistical mechanics of learning from examples (context) - Seung - 1991
50 Developments in maximum entropy data analysis (context) - Gull - 1989
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21 Generalization performance of Bayes optimal classification a.. (context) - Opper, Haussler - 1991
19 Classic maximum entropy (context) - Skilling - 1989
17 Computers and the theory of statistics: thinking the unthink.. (context) - Efron - 1979
17 Fundamentals of MaxEnt in data analysis (context) - Skilling - 1991
4 Journal of the American Statistical Association (context) - Morris - 1983
1 Journal of the Royal Statistical Society B (context) - Lindley, Smith - 1972
1 statistical mechanics (context) - Wolpert
1 Maximum entropy and the nearly black object (context) - Gull, Commentary - 1992
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