A Variable Precision Multi-granulation Rough Sets Model Based on Multiple Classification Error Rates and Constraint

摘要: In this article, a variable precision multi-granulation rough sets model based on multiple classification error rates and constraint(VMRMC) is presented aiming at the problems of single rate neglecting constraint for granular spaces existed in current theory. The VMRMC enables different granulation to be adjusted independently conformity with practical applications. It can solve more efficiently flexibility. Further, space reduction algorithm designed, which get ride irrelevant or redundant spaces. Eventually, an example illustrates validity proposed model.