An empirical comparison between stochastic and deterministic centroid initialisation for K-Means variations

Vouros, A. orcid.org/0000-0002-3383-6133, Langdell, S., Croucher, M. et al. (1 more author) (2021) An empirical comparison between stochastic and deterministic centroid initialisation for K-Means variations. Machine Learning, 110 (8). pp. 1975-2003. ISSN 0885-6125

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Copyright, Publisher and Additional Information: © 2021 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: K-Means clustering; Deterministic clustering; Benchmarking
Dates:
  • Submitted: 26 August 2019
  • Accepted: 15 June 2021
  • Published (online): 12 July 2021
  • Published: August 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 08 Jan 2020 15:17
Last Modified: 23 Aug 2021 09:57
Status: Published
Publisher: Springer Nature
Refereed: Yes
Identification Number: https://doi.org/10.1007/s10994-021-06021-7

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