|
计算机应用研究 2007
Classification Algorithm Based on Simplified Fuzzy Rules Base
|
Abstract:
Proposes a classification algorithm based on simplified fuzzy rules base combining fuzzy clustering with rough set. Firstly, generates fuzzy rules base using fuzzy clustering from numerical sample dates, and then simplifies the sample attributions using rough set theory, deletes the redundant rules, and gets the simplified fuzzy rules base, in order to make classification decision conveniently. The performance of the classification algorithm is tested by the IRIS data, and the results show that the fuzzy rules are not only comprehensive, but also have very good classification performance.