Clustering Ensemble Algorithm
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A Clustering Ensemble Algorithm is a clustering algorithm that is an ensembling algorithm (which produces a clustering ensemble).
- See: Clustering Task, Ensemble, Ensemble Learning, Consensus Clustering, Classification Ensemble Algorithm.
References
2011
- (Sammut & Webb, 2011) ⇒ Claude Sammut (editor), and Geoffrey I. Webb (editor). (2011). “Cluster Ensembles.” In: (Sammut & Webb, 2011) p.179
2005
- (Topchy et al., 2005) ⇒ Alexander Topchy, Anil K. Jain, and William Punch. (2005). “Clustering Ensembles: Models of Consensus and Weak Partitions.” In: IEEE Transactions on pattern analysis and machine intelligence, 27(12).
2004
- (Topchy et al., 2004) ⇒ Alexander Topchy, Behrouz Minaei-Bidgoli, Anil K. Jain, and William F. Punch. (2004). “Adaptive Clustering Ensembles.” In: Proceedings of the 17th International Conference on Pattern Recognition, (ICPR 2004).
- Exploratory data analysis and, in particularly, data clustering can significantly benefit from combining multiple data partitions. Clustering ensembles can offer better solutions in terms of robustness, novelty and stability [1, 2, 3]. Moreover, their parallelization capabilities can be naturally used in distributed data mining.
2003
- (Topchy et al., 2003) ⇒ A. Topchy, A.K. Jain, and W. Punch. (2003). “Combining Multiple Weak Clusterings.” In: Proceedings3d IEEE Intl. Conference on Data Mining.
2002
- (Fred & Jain, 2002) ⇒ A.L.N. Fred, and A.K. Jain. (2002). “Data Clustering Using Evidence Accumulation.” In: Proceedings of the 16th Intl. Conference on Pattern Recognition (ICPR 2002).
- (Strehl & Ghosh, 2002b) ⇒ Alexander Strehl, and Joydeep Ghosh. (2002). “Cluster Ensembles: A knowledge reuse framework for combining partitions.” In: Journal of Machine Learning Research, 3.
- (Strehl & Ghosh, 2002a) ⇒ Alexander Strehl, and Joydeep Ghosh. (2002). “Cluster Ensembles: A knowledge reuse framework for combining partitionings.” In: Proceedingsof the Conference on Artificial Intelligence (AAAI 2002).