A Clustering Preserving Transformation for k-Means Algorithm Output

2022/02/19 by Kłopotek, Mieczysław A.
#FOS: Computer and information sciences #Machine Learning (cs.LG)

paper · doi:10.48550/arxiv.2202.10455

Abstract

This note introduces a novel clustering preserving transformation of cluster sets obtained from k-means algorithm. This transformation may be used to generate new labeled datasets from existent ones. It is more flexible that Kleinberg axiom based consistency transformation because data points in a cluster can be moved away and datapoints between clusters may come closer together.

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