The Research of Extracting Minimal Decision Rules from the Decision Table in Rough Sets

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dc.contributor.authorPan, W.en
dc.contributor.authorHuang, Y.J.en
dc.contributor.authorWang, Y.S.en
dc.contributor.authorYang, H.J.en
dc.date.accessioned2012-12-17T15:57:29Z
dc.date.available2012-12-17T15:57:29Z
dc.date.issued2010
dc.description.abstractAnalyzes the traditional methods of extracting decision rules in Rough Sets, defines the concept of the decision dependability and proposes a novel algorithm of extracting short decision rules. Only the length of decision rules is extended when the current decision rules can’t classify all the samples in the decision table. At the same time, three methods are proposed to reduce the computational complexity: 1) defines the concept of bound coefficient, 2) only classify the samples with the same decision values at a time thus averting the time-consuming classification of the equivalence classes with different decision values, 3) defines the Remain set and only classify the samples in the Remain set, so the computational complexity will decrease proportional with the reduction of the samples in the Remain set. Above-mentioned methods can be used directly for incomplete information systems and have great practicability.en
dc.identifier.citationPan, W., Huang, Y.J., Wang, Y.S. and Yang, H.J. (2010) The Research of Extracting Minimal Decision Rules from the Decision Table in Rough Sets. Applied Mechanics and Materials, 44-47, pp. 3948-3953en
dc.identifier.doihttps://doi.org/10.4028/www.scientific.net/AMM.44-47.3948
dc.identifier.issn1022-6680
dc.identifier.urihttp://hdl.handle.net/2086/7956
dc.language.isoenen
dc.publisherTrans Tech Publicationsen
dc.researchgroupSoftware Technology Research Laboratory (STRL)en
dc.subjectCondition Attributeen
dc.subjectDecision Dependabilityen
dc.subjectDecision Ruleen
dc.subjectRough Seten
dc.titleThe Research of Extracting Minimal Decision Rules from the Decision Table in Rough Setsen
dc.typeArticleen

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