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JOURNALS // Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia // Archive

Dokl. RAN. Math. Inf. Proc. Upr., 2020 Volume 492, Pages 101–103 (Mi danma82)

INFORMATICS

On some factorizations of semi-metric cones and quality estimates of heuristic metrics in data analysis problems

K. V. Rudakovab

a Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russian Federation
b Center of Big Data Storage and Analysis Technology, Lomonosov Moscow State University, Moscow, Russia

Abstract: An approach is proposed to consider heuristic metrics introduced and used in data analysis problems. In the approach, the entire information on pairwise distances expressed by numerical values is reduced to information on a metric belonging as a point of a semi-metric cone to corresponding subcones, which are elements of factor sets for proposed relations of kernel equivalences for mappings into formal index families.

Keywords: smart data analysis, artificial intelligence, big data, semi-metric cone, heuristic metrics, quality estimates of metrics.

UDC: 517

Received: 09.04.2020
Revised: 09.04.2020
Accepted: 09.04.2020

DOI: 10.31857/S2686954320030236


 English version:
Doklady Mathematics, 2020, 101:3, 257–258

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