A Heuristic Program that Constructs Decision Trees

Abstract

Suppose there is a set of objects, {A, B,...E} and a set of tests, {T1, T2,...TN). When a test is applied to an object, the result is wither T or F. Assume the test may vary in cost and the object may vary in probability or occurrence. One then hopes that an unknown object may be identified by applying a sequence if tests. The appropriate test at any point in the sequence in general should depend on the results of previous tests. The problem is to construct a good test scheme using the test cost, the probabilities of occurrence, and a table of test outcomes.