An Improved Cluster Labeling Method for Support Vector Clustering

Authors:
Jaewook Lee;Daewon Lee
Affiliations:
IEEE;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2005

Citing 7
Cited 48

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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.