Аннотация
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.
Язык оригинала | английский |
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Страницы (с-по) | 712-718 |
Число страниц | 7 |
Журнал | Computer Optics |
Том | 41 |
Номер выпуска | 5 |
DOI | |
Состояние | Опубликовано - 1 сен 2017 |