Date of Award

12-1994

Document Type

Thesis

Degree Name

Master of Science in Computer Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

Dennis Ruck, PhD

Abstract

An analysis of Bayesian networks as classifiers is presented. This analysis results in an algorithm and several tools related to Bayesian network classifiers. The tools calculate and display the decision regions for two level Bayesian network classifiers. They collectively provide an approach to analyze the effects of changing network parameters on the network's decision regions. The algorithm defines a Bayesian network classifier to solve traditional classification problems. The algorithm is data driven, meaning that the resulting Bayesian network classifier is uniquely tuned to the classification problem at hand. Also, the algorithm contains procedures for defining the topology of a Bayesian network classifier and for precisely deriving the required conditional probabilities. A brief tutorial on Bayesian networks is also presented.

AFIT Designator

AFIT-GCE-ENG-94D-01

DTIC Accession Number

ADA289316

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