Publication detail

MINIMAL DECISION RULES GENERATED FROM UNCERTAIN DECISION TABLE

Authors: Jirava Pavel

Year: 2007

Type of publication: článek ve sborníku

Name of source: The 7th Annual Ph.D. Conference IMEA 2007 (Conference Paper Abstracts)

Publisher name: Univerzita Pardubice

Place: Pardubice

Page from-to: 1-10

Titles:

Language	Name	Abstract	Keywords
cze	Minimální rozhodovací pravidla generovaná z neurčité rozhodovací tabulky	V práci je navržen postup generování pravidel z neurčité rozhodovací tabulky. Neúplná/neurčitá data jsou zpracována na základě algoritmu využívajícího teorii rough množin.
eng	MINIMAL DECISION RULES GENERATED FROM UNCERTAIN DECISION TABLE	In this article we consider the problem of extracting minimal decision rules. We assume that the data are presented in the decision table and that some attribute values are lost. Decision rules can be generated directly from decision table, however in this way produced decision rules are often some attribute values unneeded. Unneeded values can be removed with using Rough sets theory, as we can see in this article. Then the final output is a set of minimal decision rules preserving information about the decision.	Rough set theory;uncertainty;information system;decision table;decision rules;approximations;attributes;decision classes.

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