A Classification Algorithm Based on Simplified Fuzzy Rules Base
This paper 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 intelligible, but also have very good classification performance.
fuzzy rules fuzzy C-means clustering rough set
Yong He
School of Management Guangdong University of Technology Guangzhou 510520 China
国际会议
2010 Third International Symposium on Knowledge Acquisition and Modeling(第三届知识获取与建模国际研讨会 KAN 2010)
武汉
英文
254-257
2010-10-20（万方平台首次上网日期，不代表论文的发表时间）