Optimization of Decision Rules Relative to Coverage - Comparative Study
In the paper, we present a modification of the dynamic programming algorithm for optimization of decision rules relative to coverage. 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.
Keywordsdecision rules coverage dynamic programming
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