On importance of rows for decision tables

Hassan Abou Eisha, Mohammad Azad*, Mikhail Moshkov

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In this paper, we propose a method for the evaluation of importance of rows for decision tables. It is based on indirect information about changes in the set of reducts after removing the considered row from the table. We also discuss results of computer experiments with decision tables from UCI Machine Learning Repository.

Original languageEnglish (US)
Title of host publicationRough Sets - International Joint Conference, IJCRS 2017, Proceedings,
EditorsDun Liu, Yiyu Yao, Beata Zielosko, Davide Ciucci, Lech Polkowski, Piotr Artiemjew, Dominik Slezak
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783319608365
StatePublished - 2017
EventInternational Joint Conference on Rough Sets, IJCRS 2017 - Olsztyn, Poland
Duration: Jul 3 2017Jul 7 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10313 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Joint Conference on Rough Sets, IJCRS 2017


  • Canonical form
  • Characteristic function
  • Decision table
  • Reduct
  • Test

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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