Reducts within the variable precision rough sets model: A further investigation

One fundamental aspect of the variable precision rough sets (VPRS) model involves a search for subsets of condition attributes which provide the same information for classification purposes as the full set of available attributes. Such subsets are labelled 'approximate reducts' or 'beta -reducts', being defined for a specified classification error denoted by beta. This paper undertakes a further investigation of the criteria for a beta -reduct within VPRS. Certain anomalies and interesting implications are identified. An additional condition is suggested for finding beta -reducts which assures a more general level knowledge equivalent to that of the full set of attributes. (C) 2001 Elsevier Science B.V. All rights reserved.