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A classification algorithm based on simplified fuzzy rules base

机译:基于简化模糊规则库的分类算法

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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.
机译: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分类算法。首先,利用模糊聚类从数值样本数据中生成模糊规则库,然后运用粗糙集理论简化样本属性,删除冗余规则,得到简化后的模糊规则库,以方便分类决策。 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易于理解,而且具有很好的分类性能。

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