Affiliations: Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia. {talha.amin, igor.chikalov, mikhail.moshkov, beata.zielosko}@kaust.edu.sa
Note: [] Address for correspondence: Institute of Comp. Sci., University of Silesia, 39, Będzińska St., Sosnowiec 41-200, Poland Also works: Institute of Computer Science, University of Silesia, 39, Będzińska St., Sosnowiec 41-200, Poland
Abstract: Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification – exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).
