Stochastic mean-shift clustering
Machine Learning
2023-12-27 v1
Abstract
In this paper we presented a stochastic version mean-shift clustering algorithm. In the stochastic version the data points "climb" to the modes of the distribution collectively, while in the deterministic mean-shift, each datum "climbs" individually, while all other data points remains in their original coordinates. Stochastic version of the mean-shift clustering is comparison with a standard (deterministic) mean-shift clustering on synthesized 2- and 3-dimensional data distributed between several Gaussian component. The comparison performed in terms of cluster purity and class data purity. It was found the the stochastic mean-shift clustering outperformed in most of the cases the deterministic mean-shift.
Keywords
Cite
@article{arxiv.2312.15684,
title = {Stochastic mean-shift clustering},
author = {Itshak Lapidot},
journal= {arXiv preprint arXiv:2312.15684},
year = {2023}
}
Comments
34 pages, 3 figures