Clustering on the cylinder, sphere and torus-Statistical machine learning approaches

Document Type

Conference Article

Publication Title

AIP Conference Proceedings

Abstract

With the advent of science and technology, manifold data are playing novel and important roles in emerging real-life challenging problems. These Big Data pose new challenges in the realm of Statistical Machine Learning, e.g. in cluster analysis or unsupervised learning (in the machine learning parlour) of directional data. In this paper, a brief overview of the some of recent clustering methods enhanced for cylindrical data, spherical data and toroidal data are presented. A new distance-based method for clustering data on the torus is also indicated.

DOI

10.1063/5.0141859

Publication Date

6-28-2023

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