Mixtures of Rectangles: Interpretable Soft Clustering
Abstract
To be eective, data-mining has to conclude with a succinct description of the data. To this end, we explore a clustering technique that nds dense regions in data. By constraining our model in a speci c way, we are able to represent the interesting regions as an intersection of intervals. This has the advantage of being easily read and understood by humans.
Cite
Text
Pelleg and Moore. "Mixtures of Rectangles: Interpretable Soft Clustering." International Conference on Machine Learning, 2001.Markdown
[Pelleg and Moore. "Mixtures of Rectangles: Interpretable Soft Clustering." International Conference on Machine Learning, 2001.](https://mlanthology.org/icml/2001/pelleg2001icml-mixtures/)BibTeX
@inproceedings{pelleg2001icml-mixtures,
title = {{Mixtures of Rectangles: Interpretable Soft Clustering}},
author = {Pelleg, Dan and Moore, Andrew W.},
booktitle = {International Conference on Machine Learning},
year = {2001},
pages = {401-408},
url = {https://mlanthology.org/icml/2001/pelleg2001icml-mixtures/}
}