modél data posterior probabiliti, P(H|D), ngagunakeun Bayes' theorem:

P(H|D) = P(D|H)P(H)/P(D)

Wates konci data-dependent P(D|H) nyaéta likelihood, jeung kadangkala disebut kajadian keur modél H; evaluasi nu bener mangrupa konci dina modél perbandingan Bayes.

Kajadian umumna normalizing constant atawa partition function tina kaputusan séjén, disebut modél paramater kaputusan H ti data D.

Hal nu asup akal di modél dua béda H1 jeung H2, parametrised ku modél vektor jeung nu ditaksir maké Bayes factor dirumuskeun ku

Sumber sejen édit

  • Gelman, A., Carlin, J.,Stern, H. and Rubin, D. Bayesian Data Analysis. Chapman and Hall/CRC.(1995)
  • Bernardo, J., and Smith, A.F.M., Bayesian Théory. John Wiley. (1994)
  • Lee, P.M. Bayesian Statistics. Arnold.(1989).
  • Denison, D.G.T., Holmes, C.C., Mallick, B.K., Smith, A.F.M., Bayesian Methods for Nonlinéar Classification and Regression. John Wiley. (2002).
  • Richard O. Duda, Peter E. Hart, David G. Stork (2000) Pattern classification (2nd edition), Section 9.6.5, p. 487-489, Wiley, ISBN 0471056693
  • Chapter 24 in Probability Theory - The logic of science by E. T. Jaynes, 1994.
  • David J.C. MacKay (2003) Information théory, inference and léarning algorithms, CUP, ISBN 0521642981, (also available online)

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