Clustering Algorithms: Taxonomy, Comparison, and Empirical Analysis in 2D Datasets

Because of the abundance of clustering methods, comparing between methods and determining which method is proper for a given dataset is crucial. Especially, the availability of huge experimental datasets and transactional and the emerging requirements for data mining and the like needs badly for clu...

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Vydané v:	Journal on artificial intelligence Ročník 2; číslo 4; s. 189 - 215
Hlavný autor:	Mostafa, Samih M
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Henderson Tech Science Press 2020
Predmet:	Algorithms Clustering Data mining Data points Datasets Empirical analysis Taxonomy Two dimensional analysis
ISSN:	2579-003X, 2579-0021, 2579-003X
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