Comparison of lazy classification algorithms based on deterministic and inhibitory decision rules

Paweł Delimata*, Mikhail Moshkov, Andrzej Skowron, Zbigniew Suraj

*Corresponding author for this work

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

8 Scopus citations

Abstract

In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules.

Original languageEnglish (US)
Title of host publicationRough Sets and Knowledge Technology - Third International Conference, RSKT 2008, Proceedings
Pages55-62
Number of pages8
DOIs
StatePublished - Jun 9 2008
Event3rd International Conference on Rough Sets and Knowledge Technology, RSKT 2008 - Chengdu, China
Duration: May 17 2008May 19 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5009 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Rough Sets and Knowledge Technology, RSKT 2008
CountryChina
CityChengdu
Period05/17/0805/19/08

Keywords

  • Decision tables
  • Deterministic decision rules
  • Inhibitory decision rules
  • Rough sets

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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