UDC 004

ON THE ISSUE OF PRACTICAL APPLICATION OF CLUSTER ANALYSIS ALGORITHMS On the issue of practical application of cluster analysis algorithms

Published in Journal of Technical Research · Volume 9, Issue 4 · Pages 11–17 · Rubric: Information technology and telecommunication
Received: 09.10.2023 Accepted: 26.01.2024 Published: 26.01.2024 Language of publication: ru-RU
Authors
Data in a broad sense refers to the factual material that provides information for the problem being studied and provides the basis for discussion, analysis and decision making. Cluster analysis is a procedure that, based on a given rule, combines objects or variables into groups. The work provides grouping of multidimensional data using such proximity measures as the sample correlation coefficient and its modulus, the cosine of the angle between vectors, and the Euclidean distance. Grouping is carried out by centers, by nearest neighbor and by selected standards. The program is written in the VS environment in C++.
cluster analysis, cluster, function of distances between vectors, dendrogram, matrix, measure of divergence, method of grouping multiple objects
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1. E.V. Gubler Primenenie neparametricheskih kriteriev statistiki v medikobiologicheskih issledovaniyah / E. V. Gubler, A. A. Genkin - L.: Medicina, 1973. - 144 s.

2. S.A. Ayvazyan, V.M. Buhshtaber, I.S. Enyukov, L.D. Meshalkin; pod red. S.A. Ayvazyana. Prikladnaya statistika. Klassifikaciya i snizhenie razmernosti - M.: Finansy i statistika, 2018. - 607 s., il.

3. Alan Agresti. An Introduction to Categorical Data Analysis. Description: Third edition. Hoboken, NJ: John Wiley & Sons, 2019. - 390 r.

4. Olenderfer M. S., Bleshfild R. K. Klasternyy analiz / Faktornyy, diskriminantnyy i klasternyy analiz: per. s angl.; Pod. red. I. S. Enyukova. - M.: Finansy i statistika, 2017. - 215 s.