A Note on Attribute Reduction in the Decision-Theoretic Rough Set Model

Authors:
Y. Zhao;S. K. Wong;Y. Y. Yao
Affiliations:
Department of Computer Science, University of Regina, Regina, Canada S4S 0A2;Department of Computer Science, University of Regina, Regina, Canada S4S 0A2;Department of Computer Science, University of Regina, Regina, Canada S4S 0A2
Venue:
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Year:
2008

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Abstract

This paper considers two groups of studies on attribute reduction in the decision-theoretic rough set model. Attribute reduction can be interpreted based on either decision preservation or region preservation. According to the fact that probabilistic regions are non-monotonic with respect to set inclusion of attributes, attribute reduction for region preservation is different from the classical interpretation of reducts.