A Note on Even-Sized Clustering Based on Optimization
説明
Some clustering methods to classify a dataset into some clusters of which the size is more than a constant K have been proposed until now. The methods are called K-member clustering and very useful for many applications. It is natural to consider clustering methods to classify a dataset into even-sized clusters, and actually, such methods have been also proposed. However, they often output inadequate results. It is considered that the reason is that they are not based on optimization. Therefore, in the previous study, we proposed Even-sized Clustering Based on Optimization (ECBO). We improved the clustering results by the simplex method to calculate the membership grade. In this study, we propose some types of extended ECBO by introducing some concept of medoid and kernel to improve ECBO.
収録刊行物
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- 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS)
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2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS) 404-409, 2016-08-01
IEEE