The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
A comparative study of efficient initialization methods for the k-means clustering algorithm
Open accessAbstract
K-means is undoubtedly the most widely used partitional clustering algorithm. Unfortunately, due to its gradient descent nature, this algorithm is highly sensitive to the initial placement of the cluster centers. Numerous initialization methods have been proposed to address this problem. In this paper, we first present an overview of these methods with an emphasis on their computational efficiency. We then compare eight commonly used linear time complexity initialization methods on a large and diverse collection of data sets using various performance criteria. Finally, we analyze the experimental results using non-parametric statistical tests and provide recommendations for practitioners. We demonstrate that popular initialization methods often perform poorly and that there are in fact strong alternatives to these methods.
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Cited by
Ikotun, A. M., Ezugwu, A. E., Abualigah, L., Abuhaija, B., & Heming, J. (2023) · Information Sciences · doi:10.1016/j.ins.2022.11.139 · Cited by 2,272
How much can k-means be improved by using better initialization and repeats?
Fränti, P., & Sieranoja, S. (2019) · Pattern Recognition · doi:10.1016/j.patcog.2019.04.014 · Cited by 451
Rashidi, H. H., Tran, N. K., Betts, E. V., Howell, L. P., & Green, R. (2019) · Academic Pathology · doi:10.1177/2374289519873088 · Cited by 371
Continental-scale animal tracking reveals functional movement classes across marine taxa
Brodie, S., Lédée, E. J. I., Heupel, M. R., Babcock, R. C., Campbell, H. A., Gledhill, D. C., Hoenner, X., Huveneers, C., Jaine, F. R. A., Simpfendorfer, C. A., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-21988-5 · Cited by 346
Woo, S. E., Jebb, A. T., Tay, L., & Parrigon, S. (2018) · Organizational Research Methods · doi:10.1177/1094428117752467 · Cited by 308
Metadata
- Authors
- Celebi, M. E., Kingravi, H. A., & Vela, P. A.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2013-01
- Volume
- 40
- Issue
- 1
- Pages
- 200-210
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2059515884
- Cited by
- 1,214
- References
- 6
- FWCI
- 34.20
- Type
- journal article
- Language
- en
- Open access
- green
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