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.
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Herman, L.M., Dollinger, M.B. Predicting effectiveness of bayesian classification systems. Psychometrika 31, 341–349 (1966). https://doi.org/10.1007/BF02289467
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DOI: https://doi.org/10.1007/BF02289467