Geodesic
The probabilistic method of finding the local-optimum of clustering
Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, no. 1 (2016), pp. 28-37

Voir la notice de l'article provenant de la source Math-Net.Ru

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. 
@article{VSPUI_2016_1_a2,
     author = {A. Lozkins and V. M. Bure},
     title = {The probabilistic method of finding the local-optimum of clustering},
     journal = {Vestnik Sankt-Peterburgskogo universiteta. Prikladna\^a matematika, informatika, processy upravleni\^a},
     pages = {28--37},
     publisher = {mathdoc},
     number = {1},
     year = {2016},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VSPUI_2016_1_a2/}
}
TY  - JOUR
AU  - A. Lozkins
AU  - V. M. Bure
TI  - The probabilistic method of finding the local-optimum of clustering
JO  - Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ
PY  - 2016
SP  - 28
EP  - 37
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/VSPUI_2016_1_a2/
LA  - ru
ID  - VSPUI_2016_1_a2
ER  - 
%0 Journal Article
%A A. Lozkins
%A V. M. Bure
%T The probabilistic method of finding the local-optimum of clustering
%J Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ
%D 2016
%P 28-37
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/VSPUI_2016_1_a2/
%G ru
%F VSPUI_2016_1_a2
A. Lozkins; V. M. Bure. The probabilistic method of finding the local-optimum of clustering. Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, no. 1 (2016), pp. 28-37. http://geodesic.mathdoc.fr/item/VSPUI_2016_1_a2/