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 recently. In this paper, an ensemble of particle swarm clustering algorithms is proposed. That is, the members of the ensemble are based on the cooperative swarms clustering approaches. The performance of the proposed particle swarm clustering ensemble is evaluated using different data sets and is compared to that of other clustering techniques. Categories and Subject Descriptors: H.3.3 [Information Search and Retrieval]: Clustering General Terms: Algorithms, Design.

• Type: Conference
• Year: 2008
• Where: GECCO
• Authors: Abbas Ahmadi, Fakhri Karray, Mohamed Kamel
• Keywords: Clustering Ensemble, GECCO 2008, Optimization, Particle Swarm Clustering, Swarm Clustering Algorithms