A feasible k-means kernel trick under non-Euclidean feature space

A feasible k-means kernel trick under non-Euclidean feature space

This paper poses the question of whether or not the usage of the kernel trick is justified. We investigate it for the special case of its usage in the kernel k-means algorithm. Kernel-k-means is a clustering algorithm, allowing clustering data in a similar way to k-means when an embedding of data po...

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Bibliographic Details
Main Authors: Kłopotek Robert, Kłopotek Mieczysław, Wierzchoń Sławomir
Format: Article
Language:English
Published: Sciendo 2020-12-01
Series:International Journal of Applied Mathematics and Computer Science
Subjects:
kernel methods
k-means
clustering
non-euclidean feature space
gower/legendre theorem
Online Access:https://doi.org/10.34768/amcs-2020-0052

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