Maximizing the Predictive Value of Production Rules
RUTGERS - THE STATE UNIV NEW BRUNSWICK NJ CENTER FOR EXPERT SYSTEMS RESEARCH
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A new approach to finding a solution for an important empirical learning problem is described. The problem is to find the single best production rule of a fixed length for classification. Predictive Value Maximization PVM, a heuristic search procedure through the space of conjunctions and disjunctions of variables and their cuttoff values, is outlined. Examples are taken from laboratory medicine, where the goal is to find the best combination of tests for making a diagnosis. Resampling techniques for estimating error rates are integrated into the PVM procedure for rule induction. Excellent results for PVM are reported on data sets previously analyzed in the AI literature using alternative classification techniques. Keywords Decision making Artificial intelligence.