Decision Rules, Trees and Tests for Tables with Many-valued Decisions–comparative Study

Mohammad Azad, Beata Zielosko, Mikhail Moshkov, Igor Chikalov

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

5 Scopus citations

Abstract

In this paper, we present three approaches for construction of decision rules for decision tables with many-valued decisions. We construct decision rules directly for rows of decision table, based on paths in decision tree, and based on attributes contained in a test (super-reduct). Experimental results for the data sets taken from UCI Machine Learning Repository, contain comparison of the maximum and the average length of rules for the mentioned approaches.
Original languageEnglish (US)
Title of host publicationProcedia Computer Science
PublisherElsevier BV
Pages87-94
Number of pages8
DOIs
StatePublished - Oct 4 2013

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