Probabilistic Evidence Accumulation for Clustering Ensembles

André Lourenço, Samuel Rota Bulò, Nicola Rebagliati, Ana Fred, Mário Figueiredo, Marcello Pelillo

2013

Abstract

Ensemble clustering methods derive a consensus partition of a set of objects starting from the results of a collection of base clustering algorithms forming the ensemble. Each partition in the ensemble provides a set of pairwise observations of the co-occurrence of objects in a same cluster. The evidence accumulation clustering paradigm uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix, which is fed to a pairwise similarity clustering algorithm to obtain a final consensus clustering. The advantage of this solution is the avoidance of the label correspondence problem, which affects other ensemble clustering schemes. In this paper we derive a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix. We introduce a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters, which are in turn estimated using a maximum likelihood approach. Additionally, we propose a novel algorithm to carry out the parameter estimation with convergence guarantees towards a local solution. Experiments on both synthetic and real benchmark data show the effectiveness of the proposed approach.

Paper Citation

in Harvard Style

Lourenço A., Rota Bulò S., Rebagliati N., Fred A., Figueiredo M. and Pelillo M. (2013). Probabilistic Evidence Accumulation for Clustering Ensembles . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 58-67. DOI: 10.5220/0004267900580067

in Bibtex Style

@conference{icpram13,
author={André Lourenço and Samuel Rota Bulò and Nicola Rebagliati and Ana Fred and Mário Figueiredo and Marcello Pelillo},
title={Probabilistic Evidence Accumulation for Clustering Ensembles},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2013},
pages={58-67},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004267900580067},
isbn={978-989-8565-41-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Probabilistic Evidence Accumulation for Clustering Ensembles
SN - 978-989-8565-41-9
AU - Lourenço A.
AU - Rota Bulò S.
AU - Rebagliati N.
AU - Fred A.
AU - Figueiredo M.
AU - Pelillo M.
PY - 2013
SP - 58
EP - 67
DO - 10.5220/0004267900580067