Geodesic
A~quantitative measure of compactness and similarity in competitive space
Sibirskij žurnal industrialʹnoj matematiki, Tome 13 (2010) no. 1, pp. 59-71

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We describe similarity measures among objects in metric and competitive spaces. We propose a competitive similarity function as a similarity measure used in classification and pattern recognition problems. This function enables us to construct some efficient algorithms for solving all main data mining problems, to obtain quantitative estimates for the compactness of images and the informativeness of trait spaces, and to construct easily interpretable decision rules. The method applies to problems with arbitrary numbers of images and characters of their distributions, and can also be used for solving poorly conditioned problems.
Keywords: similarity measure, pattern recognition, compactness, informativeness. 
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     title = {A~quantitative measure of compactness and similarity in competitive space},
     journal = {Sibirskij \v{z}urnal industrialʹnoj matematiki},
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     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/SJIM_2010_13_1_a5/}
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N. G. Zagoruǐko; I. A. Borisova; V. V. Dyubanov; O. A. Kutnenko. A~quantitative measure of compactness and similarity in competitive space. Sibirskij žurnal industrialʹnoj matematiki, Tome 13 (2010) no. 1, pp. 59-71. http://geodesic.mathdoc.fr/item/SJIM_2010_13_1_a5/