Horizontal collaborative fuzzy clustering based on similarity matrix

Yan Liu, Fusheng Yu, Jing Xu
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引用次数: 1

Abstract

The collaborative information in horizontal collaborative fuzzy clustering is transmitted by partition matrix, which requires that the dimensions of collaborating partition matrix and collaborated partition matrix must be the same. It requires that the collaborative datasets are clustered into the same number of clusters, but in many cases it is not suitable or difficult to do. In this paper, a new collaborative information transfer mechanism is proposed, which utilizes the similarity matrix to transfer the collaborative information. In this way, when the objective function is designed, the operation of the partition matrix can be transformed into the operation of the similarity matrix, so as to realize the horizontal collaborative fuzzy clustering in the case of different number of clusters. The experimental results show that the proposed algorithm is effective, which extends the application range of horizontal collaborative clustering.
基于相似矩阵的水平协同模糊聚类
水平协同模糊聚类中的协同信息是通过划分矩阵来传递的,这就要求协同划分矩阵和协同划分矩阵的维数必须相同。它要求协作数据集被聚到相同数量的聚类中,但在许多情况下,这并不合适或很难做到。本文提出了一种新的协同信息传递机制,利用相似矩阵来传递协同信息。这样,在设计目标函数时,就可以将划分矩阵的运算转化为相似矩阵的运算,从而实现不同簇数情况下的水平协同模糊聚类。实验结果表明,该算法是有效的,扩展了横向协同聚类的应用范围。
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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