Kybernetika 50 no. 5, 661-678, 2014

Consensus clustering with differential evolution

Miroslav SaboDOI: 10.14736/kyb-2014-5-0661


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.


consensus clustering, differential evolution, ensemble, data


62H30, 92G30


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