Centroid averaging algorithm for a clustering ensemble

Centroid averaging algorithm for a clustering ensemble Full article

Journal

Компьютерная оптика (Computer Optics)
ISSN: 0134-2452

Output data

Year: 2017, Volume: 41, Number: 5, Pages: 712-718 Pages count : 7 DOI: 10.18287/2412-6179-2017-41-5-712-718

Tags

Centroid; Clustering ensemble; Hyperspectral image analysis; K-means

Authors

Tatarnikov V.V. ¹ , Pestunov I.A. ² , Berikov V.B. ^1,3

Affiliations

1	Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russian Federation
2	Institute of Computational Technologies SB RAS, Novosibirsk, Russian Federation
3	Novosibirsk State University, Novosibirsk, Russian Federation

A collective approach to cluster analysis is considered in the paper. An algorithm of centroid averaging is proposed. The algorithm allows constructing the consensus partition of a dataset into clusters, using a set of partitions built with any centroid-based algorithm. We discuss results of applying the proposed algorithm to modeled data and for the segmentation of hyperspectral images with noise channels. Some details of implementation in a multithreaded environment that allows increasing the algorithm performance are given. © 2017, Institution of Russian Academy of Sciences. All rights reserved.

Tatarnikov V.V. , Pestunov I.A. , Berikov V.B.
Centroid averaging algorithm for a clustering ensemble
Компьютерная оптика (Computer Optics). 2017. V.41. N5. P.712-718. DOI: 10.18287/2412-6179-2017-41-5-712-718 WOS Scopus OpenAlex

Web of science:	WOS:000418022400014
Scopus:	2-s2.0-85037527477
OpenAlex:	W2770212813

DB	Citing
Scopus	7
OpenAlex	6
Web of science	3