Application of Dynamic Programming Approach to Optimization of Association Rules Relative to Coverage and Length
Beata Marta Zielosko · Fundamenta Informaticae · 2016
In the paper, an application of dynamic programming approach to global optimization of approximate association rules relative to coverage and length is presented. It is an extension of the dynamic programming approach to optimization of decision rules to inconsistent tables. Experimental results wi th data sets from UCI Machine Learning Repository are included.