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Clustering algorithm on high-dimension data partitional mended attribute

机译:高维数据分区修正属性的聚类算法

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In this paper, a clustering algorithm on high-dimension data partitional mended attribute is put foreword. First of all, through partition of the attribute value and discriminant degree of element, Conjunctive discriminant rules on training set are got. secondly, different discriminant rules on base of mended attribute are found. Experimental results show: the judgement rules got through the training set can better discriminate the test set. thereby, Experimental results verify the effectiveness of the proposed algorithm.
机译:本文介绍了高维数据分区修正属性的聚类算法。首先,通过分区属性值和判别程度的元素,得到了培训集的联合判别规则。其次,找到了关于修正属性基础的不同判别规则。实验结果表明:通过训练集获得了判断规则,可以更好地歧视测试集。因此,实验结果验证了所提出的算法的有效性。

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