Predicting Effectiveness of Bayesian Classification Systems
Louis M. Herman, Michael Döllinger · Psychometrika · 1966
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.