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» Fragment-based clustering ensembles
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ML
2015
ACM
4 years 1 months ago
Unsupervised ensemble minority clustering
Cluster analysis lies at the core of most unsupervised learning tasks. However, the majority of clustering algorithms depend on the all-in assumption, in which all objects belong ...
Edgar González, Jordi Turmo
ICPR
2008
IEEE
10 years 10 days 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
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
9 years 7 months ago
Particle swarm clustering ensemble
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recent...
Abbas Ahmadi, Fakhri Karray, Mohamed Kamel
SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
10 years 3 months ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee
ICDM
2010
IEEE
198views Data Mining» more  ICDM 2010»
9 years 3 months ago
Hierarchical Ensemble Clustering
Ensemble clustering has emerged as an important elaboration of the classical clustering problems. Ensemble clustering refers to the situation in which a number of different (input)...
Li Zheng, Tao Li, Chris H. Q. Ding
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