TY - JOUR

T1 - Centroid averaging algorithm for a clustering ensemble

AU - Tatarnikov, Vadim Vladimirovich

AU - Pestunov, Igor Alekseevich

AU - Berikov, Vladimir Borisovich

PY - 2017/9/1

Y1 - 2017/9/1

N2 - 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.

AB - 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.

KW - Centroid

KW - Clustering ensemble

KW - Hyperspectral image analysis

KW - K-means

UR - http://www.scopus.com/inward/record.url?scp=85037527477&partnerID=8YFLogxK

U2 - 10.18287/2412-6179-2017-41-5-712-718

DO - 10.18287/2412-6179-2017-41-5-712-718

M3 - Article

AN - SCOPUS:85037527477

VL - 41

SP - 712

EP - 718

JO - Computer Optics

JF - Computer Optics

SN - 0134-2452

IS - 5

ER -