Optimization of decision rule complexity for decision tables with many-valued decisions

Mohammad Azad, Igor Chikalov, Mikhail Moshkov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

We describe new heuristics to construct decision rules for decision tables with many-valued decisions from the point of view of length and coverage which are enough good. We use statistical test to find leaders among the heuristics. After that, we compare our results with optimal result obtained by dynamic programming algorithms. The average percentage of relative difference between length (coverage) of constructed and optimal rules is at most 6.89% (15.89%, respectively) for leaders which seems to be a promising result. © 2013 IEEE.
Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Systems, Man, and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages444-448
Number of pages5
ISBN (Print)9780769551548
DOIs
StatePublished - Oct 2013

Fingerprint Dive into the research topics of 'Optimization of decision rule complexity for decision tables with many-valued decisions'. Together they form a unique fingerprint.

Cite this