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Vestnik Sankt-Peterburgskogo Universiteta. Seriya 10. Prikladnaya Matematika. Informatika. Protsessy Upravleniya, 2016, Issue 1, Pages 28–37
(Mi vspui274)
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This article is cited in 5 scientific papers (total in 5 papers)
Applied mathematics
The probabilistic method of finding the local-optimum of clustering
A. Lozkins, V. M. Bure St. Petersburg State University, 7–9, Universitetskaya nab.,
St. Petersburg, 199034, Russia
Abstract:
The stability of clustering methods is a commonly used approach in cluster analysis for determining the “true” number of groupings. The acceptable clustering is such data sample grouping that is robust to random perturbations of investigated data. In this paper, we propose an algorithm for determining the number of clusters based on the introduction of the initial dataset which are expanded by adding the set of perturbated initial dataset. Refs 30. Figs 2.
Keywords:
clustering, cluster stability, optimal cluster number.
Received: November 26, 2015
Citation:
A. Lozkins, V. M. Bure, “The probabilistic method of finding the local-optimum of clustering”, Vestnik S.-Petersburg Univ. Ser. 10. Prikl. Mat. Inform. Prots. Upr., 2016, no. 1, 28–37
Linking options:
https://www.mathnet.ru/eng/vspui274 https://www.mathnet.ru/eng/vspui/y2016/i1/p28
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