A Novel Approach to Establishing the VPRS Model with Threshold Parameter Selection Mechanism Based on Fuzzy Algorithms

摘要

In the past, the choices of β values to be applied to find the β-reducts in VPRS for an information system are somewhat arbitrary. In this study, a systematic approach to determine the threshold value β of VPRS applied to information systems with continuous attributes is presented. The β value is directly connected to fuzzy membership functions by Implication Relations and Fuzzy Algorithms, in which the membership functions were obtained by the standard Fuzzy C-means method. The argument is that errors of system classification would occur in the fuzzy-clustering phase prior to information classification, therefore the threshold value β should be constrained by the probability of belongingness of an object to the fuzzy clusters, i.e., through the values of membership functions.