FILTA: Better View Discovery from Collections of Clusterings via Filtering
Abstract
Meta-clustering is a popular approach to find multiple clusterings in the datasest, which takes a large number of base clusterings as input for further user navigation and refinement. However, the effectiveness of meta-clustering is highly dependent on the distribution of the base clusterings and open challenges exist with regard to its stability and noise tolerance. In this paper we propose a simple and effective filtering algorithm (FILTA) that can be flexibly used in conjunction with any meta-clustering method. Given a (raw) set of base clusterings, FILTA employs information theoretic criteria to remove those having poor quality or high redundancy. Then this filtered set of clusterings is highly suitable for further exploration, particularly the use of visualization for determining the dominant views in the dataset. We evaluate FILTA on both synthetic and real world datasets, and see how its use can enhance view discovery for complex scenarios.
Cite
Text
Lei et al. "FILTA: Better View Discovery from Collections of Clusterings via Filtering." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014. doi:10.1007/978-3-662-44851-9_10Markdown
[Lei et al. "FILTA: Better View Discovery from Collections of Clusterings via Filtering." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014.](https://mlanthology.org/ecmlpkdd/2014/lei2014ecmlpkdd-filta/) doi:10.1007/978-3-662-44851-9_10BibTeX
@inproceedings{lei2014ecmlpkdd-filta,
title = {{FILTA: Better View Discovery from Collections of Clusterings via Filtering}},
author = {Lei, Yang and Nguyen, Xuan Vinh and Chan, Jeffrey and Bailey, James},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2014},
pages = {145-160},
doi = {10.1007/978-3-662-44851-9_10},
url = {https://mlanthology.org/ecmlpkdd/2014/lei2014ecmlpkdd-filta/}
}