By means of analyzing kernel clustering algorithm and rough set theory, a novel clustering algorithm, rough kernel k-means clustering algorithm, was proposed for clustering analysis.
通过研究核聚类算法,以及粗糙集,提出了一个新的用于聚类分析的粗糙核聚类方法。
The experiments indicate that the rough K-means based on self-adaptive weights is an effective rough clustering algorithm.
实验结果表明,基于自适应权重的粗糙K均值算法是一种较优的聚类算法。
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