Centroid averaging algorithm for a clustering ensemble
Tatarnikov V.V., Pestunov I.A., Berikov V.B.

 

Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia,
Institute of Computational Technologies SB RAS, Novosibirsk, Russia,
Novosibirsk State University, Novosibirsk, Russia

Full text of article: Russian language.

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Abstract:
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.

Keywords:
clustering ensemble, K-means, centroid, hyperspectral image analysis.

Citation:
Tatarnikov VV, Pestunov IA, Berikov VB. Centroid averaging algorithm for a clustering ensemble. Computer Optics 2017; 41(5): 712-718. DOI: 10.18287/2412-6179-2017-41-5-712-718.

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