A notion of stability for k-means clustering
Statistics Theory
2018-03-09 v2 Machine Learning
Statistics Theory
Abstract
In this paper, we define and study a new notion of stability for the -means clustering scheme building upon the notion of quantization of a probability measure. We connect this notion of stability to a geometric feature of the underlying distribution of the data, named absolute margin condition, inspired by recent works on the subject.
Keywords
Cite
@article{arxiv.1801.09419,
title = {A notion of stability for k-means clustering},
author = {Thibaut Le Gouic and Quentin Paris},
journal= {arXiv preprint arXiv:1801.09419},
year = {2018}
}