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Predicting Effectiveness of Bayesian Classification Systems

Published online by Cambridge University Press:  01 January 2025

Louis M. Herman  and
Michael B. Dollinger
Louis M. Herman
Affiliation:
Queens College, New York
Michael B. Dollinger
Affiliation:
University of Illinois
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Abstract

A model is presented for evaluating potential effectiveness of a Bayesian classification system using the expected value of the posterior probability for true classifications as an evaluation metric. For a given set of input parameters, the value of this complex metric is predictable from a simply computed row variance metric. Prediction equations are given for several representative sets of input parameters.

Type
Original Paper
Information
Psychometrika , Volume 31 , Issue 3 , September 1966 , pp. 341 - 349
Copyright
Copyright © 1966 Psychometric Society

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Footnotes

*

Now at the University of Hawaii.

References

Chernoff, H. and Moses, L. E. Elementary decision theory, New York: Wiley, 1959.Google Scholar
Edwards, W., Lindman, H. A., and Savage, L. J. Bayesian statistical inference for psychological research. Psychol. Rev., 1963, 70, 193–242.CrossRefGoogle Scholar
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