ck-means and fck-means: Two Deterministic Initialization Procedures for k-means Algorithm Using a Modified Crowding Distance
This paper presents two novel deterministic initialization procedures for k-means clustering based on a modified crowding distance. The procedures, named ck-means and fck-means, use more crowded points as initial centroids. Experimental studies on multiple datasets demonstrate that the proposed appr...
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| Format: | Article |
| Language: | ces |
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Prague University of Economics and Business
2023-10-01
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| Series: | Acta Informatica Pragensia |
| Subjects: | |
| Online Access: | https://aip.vse.cz/artkey/aip-202302-0011_ck-means-and-fck-means-two-deterministic-initialization-procedures-for-k-means-algorithm-using-a-modified-crow.php |
| Summary: | This paper presents two novel deterministic initialization procedures for k-means clustering based on a modified crowding distance. The procedures, named ck-means and fck-means, use more crowded points as initial centroids. Experimental studies on multiple datasets demonstrate that the proposed approach outperforms k-means and k-means++ in terms of clustering accuracy. The effectiveness of ck-means and fck-means is attributed to their ability to select better initial centroids based on the modified crowding distance. Overall, the proposed approach provides a promising alternative for improving k-means clustering. |
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| ISSN: | 1805-4951 |