Lazy classification algorithms based on deterministic and inhibitory dicision rules

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

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this chapter, we consider the same classification problem as in Chaps. 5 and 6: for a given decision table T and a new object v it is required to generate a value of the decision attribute on v using values of conditional attributes on v. We compare two lazy [1] classification algorithms based on deterministic and inhibitory decision rules of the forms (a1(x) = b1) ∧...∧ (at(x) = bt) → d(x) = b, respectively, where a1,..., at are conditional attributes, b1,..., bt are values of these attributes, d is the decision attribute and b is a value of d. By Dec (T) we denote the set of values of the decision attribute d. © 2009 Springer-Verlag Berlin Heidelberg.
Original languageEnglish (US)
JournalStudies in Computational Intelligence
Volume163
DOIs
StatePublished - Jan 1 2009
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-21

ASJC Scopus subject areas

  • Artificial Intelligence

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