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CIKM
2009
Springer
14 years 4 months ago
Fragment-based clustering ensembles
Clustering ensembles combine different clustering solutions into a single robust and stable one. Most of existing methods become highly time-consuming when the data size turns to ...
Ou Wu, Mingliang Zhu, Weiming Hu
PKDD
2010
Springer
146views Data Mining» more  PKDD 2010»
13 years 7 months ago
Nonparametric Bayesian Clustering Ensembles
Forming consensus clusters from multiple input clusterings can improve accuracy and robustness. Current clustering ensemble methods require specifying the number of consensus clust...
Pu Wang, Carlotta Domeniconi, Kathryn Blackmond La...
GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
14 years 1 months ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
AAAI
2008
14 years 4 days ago
Constraint Projections for Ensemble Learning
It is well-known that diversity among base classifiers is crucial for constructing a strong ensemble. Most existing ensemble methods obtain diverse individual learners through res...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou, Qiang ...
ICPR
2008
IEEE
14 years 4 months ago
Spectral aggregation for clustering ensemble
Since a large number of clustering algorithms exist, aggregating different clustered partitions into a single consolidated one to obtain better results has become an important pro...
Xi Wang, Chunyu Yang, Jie Zhou