Ellipsoidal <i>K</i>-Means: An Automatic Clustering Approach for Non-Uniform Data Distributions

Ellipsoidal <i>K</i>-Means: An Automatic Clustering Approach for Non-Uniform Data Distributions

Traditional <i>K</i>-means clustering assumes, to some extent, a uniform distribution of data around predefined centroids, which limits its effectiveness for many realistic datasets. In this paper, a new clustering technique, simulated-annealing-based ellipsoidal clustering (SAELLC), is...

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Bibliographic Details
Main Authors: Alaa E. Abdel-Hakim, Abdel-Monem M. Ibrahim, Kheir Eddine Bouazza, Wael Deabes, Abdel-Rahman Hedar
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Algorithms
Subjects:
unsupervised learning
data clustering
simulated annealing
silhouette function
adaptive ellipsoidal <i>K</i>-means
automatic clustering
Online Access:https://www.mdpi.com/1999-4893/17/12/551
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