Ensemble Clustering via Co-association Matrix Self-enhancement. (arXiv:2205.05937v1 [cs.LG])

Web: http://arxiv.org/abs/2205.05937

Ensemble clustering integrates a set of base clustering results to generate a
stronger one. Existing methods usually rely on a co-association (CA) matrix
that measures how many times two samples are grouped into the same cluster
according to the base clusterings to achieve ensemble clustering. However, when
the constructed CA matrix is of low quality, the performance will degrade. In
this paper, we propose a simple yet effective CA matrix self-enhancement
framework that can improve the CA matrix to achieve …

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