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
Recommended Citation
Ahlquist, Gregory C., "An Analysis of Bayesian Networks as Classifiers" (1994). Theses and Dissertations. 6368.
https://scholar.afit.edu/etd/6368