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Full-Text Articles in Physical Sciences and Mathematics
An Analysis Of Bayesian Networks As Classifiers, Gregory C. Ahlquist
An Analysis Of Bayesian Networks As Classifiers, Gregory C. Ahlquist
Theses and Dissertations
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 …
Point And Interval Estimation Of Series System Reliability Using Small Data Sets, Craig J. Willits
Point And Interval Estimation Of Series System Reliability Using Small Data Sets, Craig J. Willits
Theses and Dissertations
This investigation explored the relative performance of several small-sample point and interval estimators for series system reliability. Among point estimators, the maximum likelihood estimator MLE was compared to the corresponding Bayes estimator. In addition, four interval estimators were compared Easterlings modified maximum likelihood integer estimator, the Lindstrom-Madden estimator, and Bayesian probability interval estimators constructed using approximate beta and Bayes Monte Carlo empirical posterior densities. The relative performance of the point estimators was assessed by comparing their mean square errors. For the four interval estimators, the interval coverage probability and the average interval lower bound were examined. The values of these …