- Title
- Issues of grid-cluster retrievals in swarm-based clustering
- Creator
- Tan, Swee; Ting, Kaiming; Teng, Shyh
- Date
- 2008
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/35459
- Identifier
- vital:6383
- Identifier
-
https://doi.org/10.1109/CEC.2008.4630845
- Identifier
- ISBN:9781424418237
- Abstract
- One common approach in swarm-based clustering is to use agents to create a set of clusters on a two-dimensional grid, and then use an existing clustering method to retrieve the clusters on the grid. The second step, which we call grid-cluster retrieval, is an essential step to obtain an explicit partitioning of data. In this study, we highlight the issues in grid-cluster retrievals commonly neglected by researchers, and demonstrate the non-trivial difficulties involved. To tackle the issues, we then evaluate three methods: K-means, hierarchical clustering (Weighted Single-link) and density-based clustering (DBScan). Among the three methods, DBScan is the only method which has not been previously used for grid-cluster retrievals, yet it is shown to be the most suitable method in terms of effectiveness and efficiency.
- Publisher
- Hong Kong IEEE Press
- Relation
- Proceedings of the 2008 IEEE World Congress on Computational Intelligence p. 511-518
- Rights
- This metadata is freely available under a CCO license
- Subject
- Data mining; Particle swarm optimisation; Pattern clustering; 0801 Artificial Intelligence and Image Processing
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