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FNM-based and RFCM-based fuzzy clustering for tri-relational data

机译:基于FNM和基于RFCM的三关系数据模糊聚类

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摘要

In this paper, some fuzzy clustering methods are proposed for relational data which represents the dissimilarity for triples of data points. One method is based on the fuzzy nonmetric model and the other is on the relational fuzzy c-means. Each method has two options of fuzzification; the standard and the entropy-regularization. Through some numerical experiments, the feature of the proposed methods is discussed.
机译:本文提出了一种针对关系数据的模糊聚类方法,该方法代表了数据点三元组的不相似性。一种方法基于模糊非度量模型,另一种方法基于关系模糊c均值。每种方法都有两个模糊化选项;标准和熵正则化。通过数值实验,讨论了所提方法的特点。

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