Vestnik KRAUNC. Fiz.-Mat. Nauki. 2022. vol. 39. no. 2. pp. 136–149. ISSN 2079-6641

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MSC 68Т27

Research Article

Clustering algorithm based on feature space partitioning

M. A. Kazakov

Institute of Applied Mathematics and Automation KBSC RAS, 360000, Nalchik, Shortanova st., 89a, Russia


A new approach to robust clustering is proposed based on recursive partitioning of the feature space and density analysis. An algorithm for robust clustering of linearly inseparable points, its software implementation, as well as test results on classical data distributions are presented.

Key words: clustering, robust clustering, machine learning.

DOI: 10.26117/2079-6641-2022-39-2-136–149

Original article submitted: 05.07.2022

Revision submitted: 22.08.2022

For citation. Kazakov M. A. Clustering algorithm based on feature space partitioning. Vestnik KRAUNC. Fiz.-mat. nauki. 2022, 39: 2, 136–149. DOI: 10.26117/2079-6641-2022-39-2-136–149

Competing interests. The author declares that there are no conflicts of interest with respect to authorship and publication.

Contribution and responsibility. The author contributed to the writing of the article and is solely responsible for submitting the final version of the article to the press. The final version of the manuscript was approved by the author.

The content is published under the terms of the Creative Commons Attribution 4.0 International License (

© Kazakov M. A., 2022


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Kazakov Mukhamed Anatolevich – Junior Researcher of the Department of Neural Networks and Machine Learning, Institute of Applied Mathematics and Automation, Kabardino-Balkar Republic, Nalchik, Russia, ORCID 0000-0002-1576-1860