An Improved K-means Clustering Algorithm Towards an Efficient Data-Driven Modeling

K-means algorithm is one of the well-known unsupervised machine learning algorithms. The algorithm typically finds out distinct non-overlapping clusters in which each point is assigned to a group. The minimum squared distance technique distributes each point to the nearest clusters or subgroups. One...

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Veröffentlicht in:	Annals of data science Jg. 11; H. 5; S. 1525 - 1544
Hauptverfasser:	Zubair, Md, Iqbal, MD. Asif, Shil, Avijeet, Chowdhury, M. J. M., Moni, Mohammad Ali, Sarker, Iqbal H.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2024 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Business and Management Centroids Cluster analysis Clustering Datasets Economics Finance Insurance Machine learning Management Optimization Statistics for Business Subgroups Synthetic data Unsupervised learning Vector quantization Data Science Percentile Principal Component Analysis Machine Learning Unsupervised Algorithm K-means Clustering
ISSN:	2198-5804, 2198-5812, 2198-5812
Online-Zugang:	Volltext
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