Abstract
A general dynamic programming algorithm for converting limited, extended, or mixed entry decision tables to optimal decision trees is presented which can take into account rule frequencies or probabilities, minimum time and/or space cost criteria, common action sets, compressed rules and ELSE rules, sequencing constraints on condition tests, excludable combinations of conditions, certain ambiguities, and interrupted rule masking.
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