An Investigation of beta-Reduct Selection within the Variable Precision Rough Sets Model

Authors:
Malcolm Beynon
Affiliations:
-
Venue:
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Year:
2000

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Abstract

The Variable Precision Rough Sets Model (VPRS) is an extension of the original Rough Set Theory. To employ VPRS analysis the decision maker (DM) needs to define satisfactory levels of quality of classification and β (confidence) value. This paper considers VPRS analysis when the DM only defines a satisfactory level of quality of classification. Two criteria for selecting a β-reduct under this condition are discussed. They include the use of permissible β intervals associated with each β-reduct. An example study is given illustrating these criteria. The study is based on US state level data concerning motor vehicle traffic fatalities.