Decision rule classifiers for multi-label decision tables

Fawaz Alsolami, Mohammad Azad, Igor Chikalov, Mikhail Moshkov

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

1 Scopus citations

Abstract

Recently, multi-label classification problem has received significant attention in the research community. This paper is devoted to study the effect of the considered rule heuristic parameters on the generalization error. The results of experiments for decision tables from UCI Machine Learning Repository and KEEL Repository show that rule heuristics taking into account both coverage and uncertainty perform better than the strategies taking into account a single criterion. © 2014 Springer International Publishing.
Original languageEnglish (US)
Title of host publicationRough Sets and Intelligent Systems Paradigms
PublisherSpringer Nature
Pages191-197
Number of pages7
ISBN (Print)9783319087283
DOIs
StatePublished - 2014

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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