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Group Approach to Solving the Tasks of Recognition
Yugoslav journal of operations research, Tome 29 (2019) no. 2, p. 177 Cet article a éte moissonné depuis la source eLibrary of Mathematical Institute of the Serbian Academy of Sciences and Arts

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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. A probabilistic model of classification with the 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.
Classification : 90B85, 90C26
Keywords: Recognition, Classification, Hyper Spectral Image, Semi-Supervised Learning 
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     author = {Yedilkhan Amirgaliyev and Vladimir Berikov and Lyailya S. Cherikbayeva and Konstantin Latuta and Kalybekuuly Bekturgan},
     title = {Group {Approach} to {Solving} the {Tasks} of {Recognition}},
     journal = {Yugoslav journal of operations research},
     pages = {177 },
     year = {2019},
     volume = {29},
     number = {2},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/YJOR_2019_29_2_a1/}
}
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AU  - Yedilkhan Amirgaliyev
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AU  - Konstantin Latuta
AU  - Kalybekuuly Bekturgan
TI  - Group Approach to Solving the Tasks of Recognition
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VL  - 29
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%A Kalybekuuly Bekturgan
%T Group Approach to Solving the Tasks of Recognition
%J Yugoslav journal of operations research
%D 2019
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%G en
%F YJOR_2019_29_2_a1
Yedilkhan Amirgaliyev; Vladimir Berikov; Lyailya S. Cherikbayeva; Konstantin Latuta; Kalybekuuly Bekturgan. Group Approach to Solving the Tasks of Recognition. Yugoslav journal of operations research, Tome 29 (2019) no. 2, p. 177 . http://geodesic.mathdoc.fr/item/YJOR_2019_29_2_a1/