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Bayesian Network Classifiers

  1. Moises Goldszmidt

Published Online: 14 JAN 2011

DOI: 10.1002/9780470400531.eorms0099

Wiley Encyclopedia of Operations Research and Management Science

Wiley Encyclopedia of Operations Research and Management Science

How to Cite

Goldszmidt, M. 2011. Bayesian Network Classifiers. Wiley Encyclopedia of Operations Research and Management Science. .

Author Information

  1. Microsoft Research, Mountain View, California

Publication History

  1. Published Online: 14 JAN 2011

Abstract

Bayesian network classifiers are used extensively both in academia and in a wide range of industrial applications and domains. This article first reviews the main concepts behind statistical pattern classifiers and Bayesian networks, including the main methods for the automated induction of these models. It then continues with a description of the application of Bayesian networks as statistical pattern classifiers. It discusses the advantages of Bayesian network classifiers over other types of classifiers, and provides up-to-date references covering the material and examples of applications. Readers with basic knowledge of statistics will acquire the necessary background to explore more technical papers and decide on whether Bayesian network classifiers are the right technology for their particular problem and domain.

Keywords:

  • pattern recognition;
  • pattern classification;
  • statistics;
  • machine learning;
  • Bayesian networks;
  • graphical models;
  • model fitting;
  • maximum likelihood;
  • Bayesian methods