Question
Support Vector Machines: Kernels Explain how the use of a kernel k (a,b) enables Support Vector Machines to correctly classify all training samples, regardless of
Support Vector Machines: Kernels
Explain how the use of a kernel k (a,b) enables Support Vector Machines to correctly classify all training samples, regardless of whether they are linearly separable in their input space. How is the kernel defined in terms of feature vectors, and which properties of the mapping from input to feature vectors are essential?
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Contemporary Marketing
Authors: Louis E Boone, David L Kurtz
14th Edition
032458203X, 978-0324582031
