A Clustering Preserving Transformation for k-Means Algorithm Output. (arXiv:2202.10455v1 [cs.LG])

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 data{}sets 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.

algorithm arxiv clustering k-means transformation