Three approaches to deal with inconsistent decision tables - Comparison of decision tree complexity

Mohammad Azad, Igor Chikalov, Mikhail Moshkov

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

6 Scopus citations

Abstract

In inconsistent decision tables, there are groups of rows with equal values of conditional attributes and different decisions (values of the decision attribute). We study three approaches to deal with such tables. Instead of a group of equal rows, we consider one row given by values of conditional attributes and we attach to this row: (i) the set of all decisions for rows from the group (many-valued decision approach); (ii) the most common decision for rows from the group (most common decision approach); and (iii) the unique code of the set of all decisions for rows from the group (generalized decision approach). We present experimental results and compare the depth, average depth and number of nodes of decision trees constructed by a greedy algorithm in the framework of each of the three approaches. © 2013 Springer-Verlag.
Original languageEnglish (US)
Title of host publicationRough Sets, Fuzzy Sets, Data Mining, and Granular Computing
PublisherSpringer Nature
Pages46-54
Number of pages9
ISBN (Print)9783642412172
DOIs
StatePublished - 2013

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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