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Sibirskii Zhurnal Industrial'noi Matematiki, 2013, Volume 16, Number 1, Pages 29–41
(Mi sjim764)
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This article is cited in 8 scientific papers (total in 8 papers)
Constructing the compressed description of dataset by the function of rival similarity
N. G. Zagoruikoabc, I. A. Borisovaabc, O. A. Kutnenkobac, V. V. Dyubanovacb a Novosibirsk State University, Novosibirsk, Russia
b Sobolev Institute of Mathematics of the SDRAS, Novosibirsk, Russia
c Design Technological Institute of Digital Techniques SD RAS, Novosibirsk, Russia
Abstract:
We argue that the general aim of data mining consists in constructing some simplified compressed description of information. The Function of rival similarity (FRiS-function) is proposed as a new ternary similarity measure between objects instead of a binary one. Quantitative estimation of the compactness of datasets, basing on FRiS-function, allows constructing new more effective compressing algorithms of data mining. Some examples are described of the algorithms testing on real and model tasks.
Keywords:
data mining, function of rival similarity, pattern recognition, objects censoring, feature selection.
Received: 06.12.2012
Citation:
N. G. Zagoruiko, I. A. Borisova, O. A. Kutnenko, V. V. Dyubanov, “Constructing the compressed description of dataset by the function of rival similarity”, Sib. Zh. Ind. Mat., 16:1 (2013), 29–41; J. Appl. Industr. Math., 7:2 (2013), 275–286
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https://www.mathnet.ru/eng/sjim764 https://www.mathnet.ru/eng/sjim/v16/i1/p29
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Abstract page: | 732 | Full-text PDF : | 364 | References: | 92 | First page: | 18 |
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