Automatic Dimension Selection for a Non-negative Factorization Approach to Clustering Multiple Random Graphs
We consider a problem of grouping multiple graphs into several clusters using singular value thesholding and non-negative factorization. We derive a model selection information criterion to estimate the number of clusters. We demonstrate our approach using "Swimmer data set" as well as simulated data set, and compare its performance with two standard clustering algorithms.
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ClusteringModel SelectionSimilar Papers 제목 키워드 기반
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