Enhanced Firefly-K-Means Clustering with Adaptive Mutation and Central Limit Theorem for Automatic Clustering of High-Dimensional Datasets

Enhanced Firefly-K-Means Clustering with Adaptive Mutation and Central Limit Theorem for Automatic Clustering of High-Dimensional Datasets

Metaheuristic algorithms have been hybridized with the standard K-means to address the latter’s challenges in finding a solution to automatic clustering problems. However, the distance calculations required in the standard K-means phase of the hybrid clustering algorithms increase as the number of c...

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Bibliographic Details
Main Authors: Abiodun M. Ikotun, Absalom E. Ezugwu
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Applied Sciences
Subjects:
clustering algorithms
metaheuristic algorithms
hybrid clustering
K-means
firefly algorithms
central limit theorem
Online Access:https://www.mdpi.com/2076-3417/12/23/12275

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