Classifiers based on deterministic and inhibitory decision rules

Pawel Delimata*, Mikhail Ju Moshkov, Andrzej Skowron, Zbigniew Suraj

*Corresponding author for this work

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

4 Scopus citations

Abstract

In this chapter, we consider the following problem of classification (prediction): for a decision table T and a new object v, given by values of conditional attributes from T, it is required to generate a decision corresponding to v. We compare qualities of classifiers based on exact deterministic and inhibitory decision rules. The first type of classifiers is the following: for a given decision table we construct for each row an exact deterministic decision rule using the greedy algorithm. The obtained system of rules jointly with simple procedure of voting can be considered as a classifier. A deterministic rule, which is realizable for given object, is a vote "pro" the decision from the right-hand side of the rule.

Original languageEnglish (US)
Title of host publicationInhibitory Rules in Data Analysis
Subtitle of host publicationA Rough Set Approach
Pages81-86
Number of pages6
Volume163
DOIs
StatePublished - 2009
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume163
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

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