Group approach to solving the tasks of recognition

Autor:	Amirgaliyev Yedilkhan, Berikov Vladimir, Cherikbayeva Lyailya S., Latuta Konstantin, Bekturgan Kalybekuuly
Jazyk:	angličtina
Rok vydání:	2019
Předmět:	recognition classification hyper spectral image semi-supervised learning Management information systems T58.6-58.62
Zdroj:	Yugoslav Journal of Operations Research, Vol 29, Iss 2, Pp 177-192 (2019)
Druh dokumentu:	article
ISSN:	0354-0243 1820-743X 18082203
DOI:	10.2298/YJOR180822032Y
Popis:	In this work, we develop CASVM and CANN algorithms for semi-supervised classification problem. The algorithms are based on a combination of ensemble clustering and kernel methods. Probabilistic model of classification with use of cluster ensemble is proposed. Within the model, error probability of CANN is studied. Assumptions that make probability of error converge to zero are formulated. The proposed algorithms are experimentally tested on a hyperspectral image. It is shown that CASVM and CANN are more noise resistant than standard SVM and kNN.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/c5961a28e33a42848b1976bad445db02 Zobrazit plný text záznamu View record in DOAJ