Pairwise probabilistic clustering using evidence accumulation

Authors:
Samuel Rota Bulò;André Lourenço;Ana Fred;Marcello Pelillo
Affiliations:
Dipartimento di Informatica, University of Venice, Italy;Instituto de Telecomunicações, Lisbon, Portugal;Instituto Superior Técnico, Lisbon, Portugal and Instituto de Telecomunicações, Lisbon, Portugal;Dipartimento di Informatica, University of Venice, Italy
Venue:
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Year:
2010

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Abstract

In this paper we propose a new approach for consensus clustering which is built upon the evidence accumulation framework. Our method takes the co-association matrix as the only input and produces a soft partition of the dataset, where each object is probabilistically assigned to a cluster, as output. Our method reduces the clustering problem to a polynomial optimization in probability domain, which is attacked by means of the Baum-Eagon inequality. Experiments on both synthetic and real benchmarks data, assess the effectiveness of our approach.