Density-based Kernel Scale estimation for Kernel clustering

Kernel clustering methods have been used successfully to cluster non linearly separable data. In this paper, we propose a modification of the Kernel K-means, called the Multi-Scale Kernel K-means, that addresses one important challenge, which is the automated estimation of the kernel scale parameter... View More