Optimization of Approximate Decision Rules Relative to Coverage

We present a modification of the dynamic programming algorithm. The aims of the paper are: (i) study of the coverage of decision rules, and (ii) study of the size of a directed acyclic graph (the number of nodes and edges) for a proposed algorithm. The paper contains experimental results with decision tables from UCI Machine Learning Repository and comparison with results for the dynamic programming algorithm.

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