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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Bibliographic Details

Published in:	Journal on artificial intelligence Vol. 2; no. 4; pp. 189 - 215
Main Author:	Mostafa, Samih M
Format:	Journal Article
Language:	English
Published:	Henderson Tech Science Press 2020
Subjects:	Algorithms Clustering Data mining Data points Datasets Empirical analysis Taxonomy Two dimensional analysis
ISSN:	2579-003X, 2579-0021, 2579-003X
Online Access:	Get full text
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