Cluster validity indices for automatic clustering: A comprehensive review
The Cluster Validity Index is an integral part of clustering algorithms. It evaluates inter-cluster separation and intra-cluster cohesion of candidate clusters to determine the quality of potential solutions. Several cluster validity indices have been suggested for both classical clustering algorith...
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| Language: | English |
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Elsevier
2025-01-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025003330 |
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| author | Abiodun M. Ikotun Faustin Habyarimana Absalom E. Ezugwu |
| author_facet | Abiodun M. Ikotun Faustin Habyarimana Absalom E. Ezugwu |
| author_sort | Abiodun M. Ikotun |
| collection | DOAJ |
| description | The Cluster Validity Index is an integral part of clustering algorithms. It evaluates inter-cluster separation and intra-cluster cohesion of candidate clusters to determine the quality of potential solutions. Several cluster validity indices have been suggested for both classical clustering algorithms and automatic metaheuristic-based clustering algorithms. Different cluster validity indices exhibit different characteristics based on the mathematical models they employ in determining the values for the various cluster attributes. Metaheuristic-based automatic clustering algorithms use cluster validity index as a fitness function in its optimization procedure to evaluate the candidate cluster solution's quality. A systematic review of the cluster validity indices used as fitness functions in metaheuristic-based automatic clustering algorithms is presented in this study. Identifying, reporting, and analysing various cluster validity indices is important in classifying the best CVIs for optimum performance of a metaheuristic-based automatic clustering algorithm. This review also includes an experimental study on the performance of some common cluster validity indices on some synthetic datasets with varied characteristics as well as real-life datasets using the SOSK-means automatic clustering algorithm. This review aims to assist researchers in identifying and selecting the most suitable cluster validity indices (CVIs) for their specific application areas. |
| format | Article |
| id | doaj-art-3c9f6e03bdee44d9be9645292a9ca4b7 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-3c9f6e03bdee44d9be9645292a9ca4b72025-02-02T05:28:38ZengElsevierHeliyon2405-84402025-01-01112e41953Cluster validity indices for automatic clustering: A comprehensive reviewAbiodun M. Ikotun0Faustin Habyarimana1Absalom E. Ezugwu2School of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal, King Edward Avenue, Pietermaritzburg Campus, Pietermaritzburg, 3201, KwaZulu-Natal, South AfricaSchool of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal, King Edward Avenue, Pietermaritzburg Campus, Pietermaritzburg, 3201, KwaZulu-Natal, South AfricaUnit for Data Science and Computing, North-West University, 11 Hoffman Street, Potchefstroom, 2520, North-West, South Africa; Corresponding author.The Cluster Validity Index is an integral part of clustering algorithms. It evaluates inter-cluster separation and intra-cluster cohesion of candidate clusters to determine the quality of potential solutions. Several cluster validity indices have been suggested for both classical clustering algorithms and automatic metaheuristic-based clustering algorithms. Different cluster validity indices exhibit different characteristics based on the mathematical models they employ in determining the values for the various cluster attributes. Metaheuristic-based automatic clustering algorithms use cluster validity index as a fitness function in its optimization procedure to evaluate the candidate cluster solution's quality. A systematic review of the cluster validity indices used as fitness functions in metaheuristic-based automatic clustering algorithms is presented in this study. Identifying, reporting, and analysing various cluster validity indices is important in classifying the best CVIs for optimum performance of a metaheuristic-based automatic clustering algorithm. This review also includes an experimental study on the performance of some common cluster validity indices on some synthetic datasets with varied characteristics as well as real-life datasets using the SOSK-means automatic clustering algorithm. This review aims to assist researchers in identifying and selecting the most suitable cluster validity indices (CVIs) for their specific application areas.http://www.sciencedirect.com/science/article/pii/S2405844025003330ClusteringCluster validity indexAutomatic clusteringMetaheuristic algorithmsOptimization algorithms |
| spellingShingle | Abiodun M. Ikotun Faustin Habyarimana Absalom E. Ezugwu Cluster validity indices for automatic clustering: A comprehensive review Heliyon Clustering Cluster validity index Automatic clustering Metaheuristic algorithms Optimization algorithms |
| title | Cluster validity indices for automatic clustering: A comprehensive review |
| title_full | Cluster validity indices for automatic clustering: A comprehensive review |
| title_fullStr | Cluster validity indices for automatic clustering: A comprehensive review |
| title_full_unstemmed | Cluster validity indices for automatic clustering: A comprehensive review |
| title_short | Cluster validity indices for automatic clustering: A comprehensive review |
| title_sort | cluster validity indices for automatic clustering a comprehensive review |
| topic | Clustering Cluster validity index Automatic clustering Metaheuristic algorithms Optimization algorithms |
| url | http://www.sciencedirect.com/science/article/pii/S2405844025003330 |
| work_keys_str_mv | AT abiodunmikotun clustervalidityindicesforautomaticclusteringacomprehensivereview AT faustinhabyarimana clustervalidityindicesforautomaticclusteringacomprehensivereview AT absalomeezugwu clustervalidityindicesforautomaticclusteringacomprehensivereview |