Probabilistic consensus clustering using evidence accumulation
| LEADER | caa a22 4500 | ||
|---|---|---|---|
| 001 | 605478112 | ||
| 003 | CHVBK | ||
| 005 | 20210128100404.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150101xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s10994-013-5339-6 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s10994-013-5339-6 | ||
| 245 | 0 | 0 | |a Probabilistic consensus clustering using evidence accumulation |h [Elektronische Daten] |c [André Lourenço, Samuel Rota Bulò, Nicola Rebagliati, Ana Fred, Mário Figueiredo, Marcello Pelillo] |
| 520 | 3 | |a Clustering ensemble methods produce a consensus partition of a set of data points by combining the results of a collection of base clustering algorithms. In the evidence accumulation clustering (EAC) paradigm, the clustering ensemble is transformed into a pairwise co-association matrix, thus avoiding the label correspondence problem, which is intrinsic to other clustering ensemble schemes. In this paper, we propose a consensus clustering approach based on the EAC paradigm, which is not limited to crisp partitions and fully exploits the nature of the co-association matrix. Our solution determines probabilistic assignments of data points to clusters by minimizing a Bregman divergence between the observed co-association frequencies and the corresponding co-occurrence probabilities expressed as functions of the unknown assignments. We additionally propose an optimization algorithm to find a solution under any double-convex Bregman divergence. Experiments on both synthetic and real benchmark data show the effectiveness of the proposed approach. | |
| 540 | |a The Author(s), 2013 | ||
| 690 | 7 | |a Consensus clustering |2 nationallicence | |
| 690 | 7 | |a Evidence Accumulation |2 nationallicence | |
| 690 | 7 | |a Ensemble clustering |2 nationallicence | |
| 690 | 7 | |a Bregman divergence |2 nationallicence | |
| 700 | 1 | |a Lourenço |D André |u Instituto Superior de Engenharia de Lisboa, Lisboa, Portugal |4 aut | |
| 700 | 1 | |a Rota Bulò |D Samuel |u DAIS, via Torino, 155, Mestre, Venezia, Italy |4 aut | |
| 700 | 1 | |a Rebagliati |D Nicola |u VTT Technical Research Center of Finland, P.O. Box 1000, 02044, VTT, Finland |4 aut | |
| 700 | 1 | |a Fred |D Ana |u Instituto de Telecomunicações, Lisboa, Portugal |4 aut | |
| 700 | 1 | |a Figueiredo |D Mário |u Instituto de Telecomunicações, Lisboa, Portugal |4 aut | |
| 700 | 1 | |a Pelillo |D Marcello |u DAIS, via Torino, 155, Mestre, Venezia, Italy |4 aut | |
| 773 | 0 | |t Machine Learning |d Springer US; http://www.springer-ny.com |g 98/1-2(2015-01-01), 331-357 |x 0885-6125 |q 98:1-2<331 |1 2015 |2 98 |o 10994 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s10994-013-5339-6 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s10994-013-5339-6 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Lourenço |D André |u Instituto Superior de Engenharia de Lisboa, Lisboa, Portugal |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Rota Bulò |D Samuel |u DAIS, via Torino, 155, Mestre, Venezia, Italy |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Rebagliati |D Nicola |u VTT Technical Research Center of Finland, P.O. Box 1000, 02044, VTT, Finland |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Fred |D Ana |u Instituto de Telecomunicações, Lisboa, Portugal |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Figueiredo |D Mário |u Instituto de Telecomunicações, Lisboa, Portugal |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Pelillo |D Marcello |u DAIS, via Torino, 155, Mestre, Venezia, Italy |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Machine Learning |d Springer US; http://www.springer-ny.com |g 98/1-2(2015-01-01), 331-357 |x 0885-6125 |q 98:1-2<331 |1 2015 |2 98 |o 10994 | ||