Application of Dynamic Programming Approach to Optimization of Association Rules Relative to Coverage and Length

Issue title: Rough Sets, Rule-Based Approaches, and Knowledge Representation

Guest editors: Davide Ciucci, Dominik Ślęzak and Marcin Wolski

Article type: Research Article

Authors: Zielosko, Beata^*

Affiliations: Institute of Computer Science, University of Silesia, 39, Będzińska St., 41-200 Sosnowiec, Poland. beata.zielosko@us.edu.pl

Correspondence: [*] Address for correspondence: Institute of Computer Science, University of Silesia 39, Będzińska St., 41-200 Sosnowiec, Poland

Abstract: 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 with data sets from UCI Machine Learning Repository are included.

Keywords: Rough sets, association rules, decision rules, length, coverage, dynamic programming

DOI: 10.3233/FI-2016-1424

Journal: Fundamenta Informaticae, vol. 148, no. 1-2, pp. 87-105, 2016