Name
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14980-1_38 | SSPR/SPR |
Keywords | Field | DocType |
polynomial optimization,pairwise probabilistic,probability domain,real benchmarks data,soft partition,evidence accumulation framework,co-association matrix,consensus clustering,new approach,clustering problem,baum-eagon inequality | k-medians clustering,Pairwise comparison,Fuzzy clustering,Data mining,Correlation clustering,Matrix (mathematics),Consensus clustering,Cluster analysis,Partition (number theory),Mathematics | Conference |
Volume | ISSN | ISBN |
6218 | 0302-9743 | 3-642-14979-0 |
Citations | PageRank | References |
10 | 0.53 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samuel Rota Bulò | 1 | 564 | 33.69 |
| André Lourenço | 2 | 312 | 45.33 |
| Ana Fred | 3 | 216 | 17.07 |
| Marcello Pelillo | 4 | 1888 | 150.33 |