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What is Supervised k-Means Clustering Methods about?

The document discusses a supervised learning approach to enhance the k-means clustering algorithm by training a distance measure using structural support vector machines (SSVM). It presents two computationally efficient variants of the method and provides theoretical and empirical analyses demonstrating improved clustering accuracy. The paper also contrasts supervised clustering with semi-supervised clustering and outlines the challenges in parameterizing similarity measures for effective clustering.

Author

u695788

Language

EN