Geodesic
Constructing the compressed description of dataset by the function of rival similarity
Sibirskij žurnal industrialʹnoj matematiki, Tome 16 (2013) no. 1, pp. 29-41

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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. 
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     author = {N. G. Zagoruiko and I. A. Borisova and O. A. Kutnenko and V. V. Dyubanov},
     title = {Constructing the compressed description of dataset by the function of rival similarity},
     journal = {Sibirskij \v{z}urnal industrialʹnoj matematiki},
     pages = {29--41},
     publisher = {mathdoc},
     volume = {16},
     number = {1},
     year = {2013},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/SJIM_2013_16_1_a3/}
}
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N. G. Zagoruiko; I. A. Borisova; O. A. Kutnenko; V. V. Dyubanov. Constructing the compressed description of dataset by the function of rival similarity. Sibirskij žurnal industrialʹnoj matematiki, Tome 16 (2013) no. 1, pp. 29-41. http://geodesic.mathdoc.fr/item/SJIM_2013_16_1_a3/