A classification algorithm based on simplified fuzzy rules base

Yong He
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Abstract

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.
一种基于简化模糊规则库的分类算法
本文提出了一种基于模糊聚类和粗糙集相结合的简化模糊规则库的分类算法。首先对数值样本数据进行模糊聚类生成模糊规则库,然后利用粗糙集理论对样本属性进行简化,剔除冗余规则,得到简化后的模糊规则库,便于分类决策。通过IRIS数据对分类算法的性能进行了测试,结果表明模糊规则不仅具有可理解性,而且具有很好的分类性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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