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

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dc.contributor.author Pan, W. en
dc.contributor.author Huang, Y.J. en
dc.contributor.author Wang, Y.S. en
dc.contributor.author Yang, H.J. en
dc.date.accessioned 2012-12-17T15:57:29Z
dc.date.available 2012-12-17T15:57:29Z
dc.date.issued 2010
dc.identifier.citation Pan, 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. 3948-3953 en
dc.identifier.issn 1022-6680
dc.identifier.uri http://hdl.handle.net/2086/7956
dc.description.abstract Analyzes 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.language.iso en en
dc.publisher Trans Tech Publications en
dc.subject Condition Attribute en
dc.subject Decision Dependability en
dc.subject Decision Rule en
dc.subject Rough Set en
dc.title The Research of Extracting Minimal Decision Rules from the Decision Table in Rough Sets en
dc.type Article en
dc.identifier.doi http://dx.doi.org/10.4028/www.scientific.net/AMM.44-47.3948
dc.researchgroup Software Technology Research Laboratory (STRL) en


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