Performance evaluation results of evolutionary clustering algorithm star for clustering heterogeneous datasets

This article presents the data used to evaluate the performance of evolutionary clustering algorithm star (ECA*) compared to five traditional and modern clustering algorithms. Two experimental methods are employed to examine the performance of ECA* against genetic algorithm for clustering++ (GENCLUS...

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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Hassan, Bryar A, Rashid, TarikA, Mirjalili, Seyedali
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 30.04.2021
Schlagworte:	Algorithms Clustering Datasets Evolutionary algorithms Genetic algorithms Learning vector quantization networks Machine learning Performance evaluation Performance rating
ISSN:	2331-8422
Online-Zugang:	Volltext
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