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Classification Algorithm Based on Simplified Fuzzy Rules Base
一种基于精简的模糊规则库的分类算法*

Keywords: Fuzzy Rules,Fuzzy C-Means Clustering,Rough Set
模糊规则
,模糊C均值聚类,粗糙集,精简,模糊规则库,分类算法,Based,Rules,Fuzzy,Algorithm,分类效果,仿真测试,IRIS,分类决策,冗余规则,删除,约简,属性,样本数据,粗糙集理论,运用,数值型,模糊聚类

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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.

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