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.
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References
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Beynon, M.J. (2003). Degree of Dependency and Quality of Classification in the Extended Variable Precision Rough Sets Model. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_40
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DOI: https://doi.org/10.1007/3-540-39205-X_40
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