Consistency constraints for overlapping data clustering
Machine Learning
2016-08-16 v1 Machine Learning
Abstract
We examine overlapping clustering schemes with functorial constraints, in the spirit of Carlsson--Memoli. This avoids issues arising from the chaining required by partition-based methods. Our principal result shows that any clustering functor is naturally constrained to refine single-linkage clusters and be refined by maximal-linkage clusters. We work in the context of metric spaces with non-expansive maps, which is appropriate for modeling data processing which does not increase information content.
Cite
@article{arxiv.1608.04331,
title = {Consistency constraints for overlapping data clustering},
author = {Jared Culbertson and Dan P. Guralnik and Jakob Hansen and Peter F. Stiller},
journal= {arXiv preprint arXiv:1608.04331},
year = {2016}
}
Comments
12 pages