(1946). Probability, frequency and reasonable expectation. Ameri can Journal of Physics, 14:1 13.
(1986). Probability and statistics. Reading, MA: Addison Wesley.
(1995). Supervised and unsupervised discretization of continuous features, In A. Prieditis and S.Russell (eds.), Proceedings of the Twelfth International Conference on Machine Learning, pp. 194 202. San Francisco, CA: Morgan Kaufmann.
(1999). Learning Bayesian networks with local structure. In M.I. Jordan (ed.), Learning in graphical models. Cambridge, MA: MIT Press.
(1997). Bayesian network classifiers. Machine Learning, :131 163.
(1995). Bayesian Data Analysis, Chapman & Hall/CRC.
(1994). Learning Bayesian networks: The combination of knowledge and statistical data. Technical Report MSR-TR-94-09, Microsoft Research.
(1996). Probability theory: The logic of science, Fragmentary Edition. Available online at: http://bayes.wustl.edu/etj/prob.html.
(1996). A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization. Technical Report CMU-CS-96-118, School of Computer Science, Carnegie Mellon University, March.
(1997). Improving simple Bayes. ECML-97: Proceedings of the Ninth European Conference on Machine Learning.
(1994). Learning Bayesian networks: An approach based on the MDL principle Computational Intelligence (3), 269 293.
(1988). Local computations with probabilities on graphical structures and their application to expert systems. Journal of the Royal Statistical Society, Series B, (2):157 224.
(1997). Machine learning. New York: McGraw-Hill.
(1993). Probabilistic inference using Markov Chain Monte Carlo Methods. Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto.
(1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Mateo, CA: Morgan Kaufmann.
(1999). Bayesian methods for intelligent data analysis. In M. Berthold & D.J. Hand, (eds.), Intelligent data analysis: An introduction. New York: Springer-Verlag.
(1999). An introduction to Markov Chain Monte Carlo. Available online at: http://omega.albany.edu:8008/cdocs/.
(1996). Data analysis: A Bayesian tutorial. Oxford, UK: Oxford Science Publications.
(1996). Bayesian belief networks: Odds and ends. Technical Report UU-Cs-1996-14, Utretch University.
(2000). Data mining: Practical machine learning tools and techniques with Java implementations. San Mateo, CA: Morgan Kaufmann.
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