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Consensus clustering with differential evolution. (English) Zbl 1308.62132
Summary: Consensus clustering algorithms are used to improve properties of traditional clustering methods, especially their accuracy and robustness. In this article, we introduce our approach that is based on a refinement of the set of initial partitions and uses differential evolution algorithm in order to find the most valid solution. Properties of the algorithm are demonstrated on four benchmark datasets.
MSC:
62H30 Classification and discrimination; cluster analysis (statistical aspects)
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