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Issue No.03 - March (2005 vol.27)
pp: 461-464
ABSTRACT
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.
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 & Machine Intelligence, vol.27, no. 3, pp. 461-464, March 2005, doi:10.1109/TPAMI.2005.47
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