An Algorithmic Introduction to Clustering
Machine Learning
2020-06-11 v1 Machine Learning
Abstract
This paper tries to present a more unified view of clustering, by identifying the relationships between five different clustering algorithms. Some of the results are not new, but they are presented in a cleaner, simpler and more concise way. To the best of my knowledge, the interpretation of DBSCAN as a climbing procedure, which introduces a theoretical connection between DBSCAN and Mean shift, is a novel result.
Cite
@article{arxiv.2006.04916,
title = {An Algorithmic Introduction to Clustering},
author = {Bernardo A. Gonzalez-Torres},
journal= {arXiv preprint arXiv:2006.04916},
year = {2020}
}
Comments
26 pages, 14 figures