Bayesian Artificial Intelligence 2nd ed - K. Korb, A. Nicholson (CRC, 2011) WW.pdf

Bayesian
Artificial
Intelligence
SECOND EDITION
Chapman & Hall/CRC
Computer Science and Data Analysis Series
The interface between puter and statistical sciences is increasing, as each discipline
seeks to harness the power and resources of the other. This series aims to foster the integration
between puter sciences and statistical, numerical, and probabilistic methods by
publishing a broad range of reference works, textbooks, and handbooks.
SERIES EDITORS
David Blei, Princeton University
David Madigan, Rutgers University
Marina Meila, University of Washington
Fionn Murtagh, Royal Holloway, University of London
Proposals for the series should be sent directly to one of the series editors above, or submitted to:
Chapman & Hall/CRC
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Published Titles
Bayesian Artificial Intelligence, Second Edition Introduction to Machine Learning
Kevin B. Korb and Ann E. Nicholson â and Bioinformatics
Clustering for Data Mining: Sushmita Mitra, Sujay Datta,
â A Data Recovery Approach â Theodore Perkins, and e Michailidis
Boris Mirkin Microarray Image Analysis:
Computational Statistics Handbook with â An Algorithmic Approach
â MATLAB®, Second Edition Karl Fraser, Zidong Wang, and Xiaohui Liu
Wendy L. Martinez and Angel R. Martinez Pattern Recognition Algorithms for
Correspondence Analysis and Data â Data Mining
â Coding with Java and R Sankar K. Pal and Pabitra Mitra
Fionn Murtagh R Graphics
Design and Modeling puter Paul Murrell
â Experiments R Programming for Bioinformatics
Kai-Tai Fang, Runze Li, and Agus Sudjianto Robert Gentleman
®
Exploratory Data Analysis with MATLAB Semisupervised Learning for
Wendy L. Martinez and Angel R. Martinez putational Linguistics
Exploratory Multivariate Analysis by Steven Abney
â Example Using R puting with R
François Husson, Sébastien Lê, and Maria L. Rizzo
â Jérôme Pagès
Introduction to Data Technologies
Paul Murrell
Bayes