Degree of Dependency and Quality of Classification in the Extended Variable Precision Rough Sets Model Proceedings

Beynon, Malcolm James ORCID: https://orcid.org/0000-0002-5757-270X 2003. Degree of Dependency and Quality of Classification in the Extended Variable Precision Rough Sets Model Proceedings. Presented at: 9th International Conference Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, Chongqing, China, 26-29 May 2003. Published in: Wang, Guoyin, Liu, Qing, Yao, Yiyu and Skowron, Andrzej eds. Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 9th International Conference, RSFDGrC 2003, Chongqing, China, May 26-29, 2003 Proceedings. Lecture Notes in Computer Science (2639) Berlin: Springer, pp. 287-290. 10.1007/3-540-39205-X_40

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Abstract

In this paper an investigation on the utilisation of the degree of dependency and quality of classification measures in the extended variable precision rough sets model is undertaken. The use of (l, u)-graphs enable these measures to aid in the classification of objects to a number of categories for a choice of l and u values and selection of a (l, u)-reduct.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Publisher:	Springer
ISBN:	9783540140405
Related URLs:	Publisher
Last Modified:	21 Oct 2022 09:42
URI:	https://orca.cardiff.ac.uk/id/eprint/37438

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