An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Machine Learning
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This work presents a short introduction to the main ideas behind the design of specific kernel functions when used by machine learning algorithms, for example support vector machines, in the case that involved patterns are described by non-vectorial information. In particular the interval data case will be analysed as an illustrating example: explicit kernels based on the centre-radius diagram will be formulated for closed bounded intervals in the real line.