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We discuss novel clustering methods that are based on mapping data points to a Hilbert space by means of a Gaussian kernel. The first method, support vector clustering (SVC), searches for the smallest sphere enclosing data images in Hilbert space. The second, quantum clustering (QC), searches...
Persistent link: https://www.econbiz.de/10011064367