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An Improved Cluster Labeling Method for Support Vector Clustering
March 2005 (vol. 27 no. 3)
pp. 461-464
The support vector clustering (SVC) algorithm is a recently emerged unsupervised learning method inspired by support vector machines. One key step involved in the SVC algorithm is the cluster assignment of each data point. A new cluster labeling method for SVC is developed based on some invariant topological properties of a trained kernel radius function. Benchmark results show that the proposed method outperforms previously reported labeling techniques.

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Index Terms:
Clustering, unsupervised learning method, support vector machines.
Citation:
Jaewook Lee, Daewon Lee, "An Improved Cluster Labeling Method for Support Vector Clustering," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 3, pp. 461-464, March 2005, doi:10.1109/TPAMI.2005.47
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