Variance-k-means++: A deterministic centroid initialization method based on variance for enhanced clustering stability.
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| Title: | Variance-k-means++: A deterministic centroid initialization method based on variance for enhanced clustering stability. |
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| Authors: | Widodo1,2 widodo@unj.ac.id, Ramadhan, Jiel Vayyad1,2 jielvayad261102@gmail.com, Duskarnaen, Muhammad Ficky1 duskarnaen@unj.ac.id, Fauziastuti, Via Tuhamah1 viatuhamah@unj.ac.id, Pondayu, Chelsea Zaomi1,2 chelseazaomi9@gmail.com, Septianda, Mada Rekadarma1,2 mada.septianda@gmail.com |
| Source: | International Journal of Electrical & Computer Engineering (2088-8708). Jun2026, Vol. 16 Issue 3, p1434-1448. 14p. |
| Subjects: | K-means clustering, Centroid, Clustering algorithms, Optimization algorithms, Deviation (Statistics), Deterministic algorithms |
| Abstract: | K-means++ is developed to improve the performance of k-means when choosing a starting centroid. However, both algorithms in clustering still select an initial centroid randomly. Randomly selecting initial centroids has the potential to produce unstable clusters. This paper proposes a deterministic centroid initialization method called variance-k-means++, which utilizes statistical properties--mean and variance--to generate pseudo-centroids and derive initial centroids. The method aims to improve clustering stability and reduce the number of iterations. For the initial study, we used low-dimensional data to conduct the experiment series. Then, we employed two baseline methods for benchmarking, k-means and k-means++. The results show that variance-k-means++ outperformed the baseline method on average. Evaluating in Davies-Bouldin index (DBI) and convergence analysis, we obtained DBI values at 0.756 and 0,771 for vertical and horizontal variance k-means++ with Iris dataset. At the same time, baseline methods have 0.802 and 0.830 for k-means++ and k-means, respectively. In convergence analysis, the results are 5.158 for vertical and 5.474 for horizontal, while baseline methods are 9.000 and 8.842. The primary contribution of this study lies in its achievement of minimizing the number of iterations while enhancing cluster stability. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: Variance-k-means++: A deterministic centroid initialization method based on variance for enhanced clustering stability. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Widodo%22">Widodo</searchLink><relatesTo>1,2</relatesTo><i> widodo@unj.ac.id</i><br /><searchLink fieldCode="AR" term="%22Ramadhan%2C+Jiel+Vayyad%22">Ramadhan, Jiel Vayyad</searchLink><relatesTo>1,2</relatesTo><i> jielvayad261102@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Duskarnaen%2C+Muhammad+Ficky%22">Duskarnaen, Muhammad Ficky</searchLink><relatesTo>1</relatesTo><i> duskarnaen@unj.ac.id</i><br /><searchLink fieldCode="AR" term="%22Fauziastuti%2C+Via+Tuhamah%22">Fauziastuti, Via Tuhamah</searchLink><relatesTo>1</relatesTo><i> viatuhamah@unj.ac.id</i><br /><searchLink fieldCode="AR" term="%22Pondayu%2C+Chelsea+Zaomi%22">Pondayu, Chelsea Zaomi</searchLink><relatesTo>1,2</relatesTo><i> chelseazaomi9@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Septianda%2C+Mada+Rekadarma%22">Septianda, Mada Rekadarma</searchLink><relatesTo>1,2</relatesTo><i> mada.septianda@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Electrical+%26+Computer+Engineering+%282088-8708%29%22">International Journal of Electrical & Computer Engineering (2088-8708)</searchLink>. Jun2026, Vol. 16 Issue 3, p1434-1448. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22K-means+clustering%22">K-means clustering</searchLink><br /><searchLink fieldCode="DE" term="%22Centroid%22">Centroid</searchLink><br /><searchLink fieldCode="DE" term="%22Clustering+algorithms%22">Clustering algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Deviation+%28Statistics%29%22">Deviation (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Deterministic+algorithms%22">Deterministic algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: K-means++ is developed to improve the performance of k-means when choosing a starting centroid. However, both algorithms in clustering still select an initial centroid randomly. Randomly selecting initial centroids has the potential to produce unstable clusters. This paper proposes a deterministic centroid initialization method called variance-k-means++, which utilizes statistical properties--mean and variance--to generate pseudo-centroids and derive initial centroids. The method aims to improve clustering stability and reduce the number of iterations. For the initial study, we used low-dimensional data to conduct the experiment series. Then, we employed two baseline methods for benchmarking, k-means and k-means++. The results show that variance-k-means++ outperformed the baseline method on average. Evaluating in Davies-Bouldin index (DBI) and convergence analysis, we obtained DBI values at 0.756 and 0,771 for vertical and horizontal variance k-means++ with Iris dataset. At the same time, baseline methods have 0.802 and 0.830 for k-means++ and k-means, respectively. In convergence analysis, the results are 5.158 for vertical and 5.474 for horizontal, while baseline methods are 9.000 and 8.842. The primary contribution of this study lies in its achievement of minimizing the number of iterations while enhancing cluster stability. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.11591/ijece.v16i3.pp1434-1448 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1434 Subjects: – SubjectFull: K-means clustering Type: general – SubjectFull: Centroid Type: general – SubjectFull: Clustering algorithms Type: general – SubjectFull: Optimization algorithms Type: general – SubjectFull: Deviation (Statistics) Type: general – SubjectFull: Deterministic algorithms Type: general Titles: – TitleFull: Variance-k-means++: A deterministic centroid initialization method based on variance for enhanced clustering stability. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Widodo – PersonEntity: Name: NameFull: Ramadhan, Jiel Vayyad – PersonEntity: Name: NameFull: Duskarnaen, Muhammad Ficky – PersonEntity: Name: NameFull: Fauziastuti, Via Tuhamah – PersonEntity: Name: NameFull: Pondayu, Chelsea Zaomi – PersonEntity: Name: NameFull: Septianda, Mada Rekadarma IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20888708 Numbering: – Type: volume Value: 16 – Type: issue Value: 3 Titles: – TitleFull: International Journal of Electrical & Computer Engineering (2088-8708) Type: main |
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