Support Vector Machines use kernel functions to do all the hard work and this StatQuest dives deep into one of the most popular: The Radial (RBF) Kernel. We talk about the parameter values, how they calculate high-dimensional coordinates and then we'll figure out, step-by-step, how the Radial Kernel works in infinite dimensions.
NOTE: This StatQuest assumes you already know about...
Support Vector Machines: https://youtu.be/efR1C6CvhmE
Cross Validation: https://youtu.be/fSytzGwwBVw
The Polynomial Kernel: https://youtu.be/Toet3EiSFcM
ALSO NOTE: This StatQuest is based on...
1) The description of Kernel Functions, and associated concepts on pages 352 to 353 of the Introduction to Statistical Learning in R: http://faculty.marshall.usc.edu/gareth-james/ISL/
2) The derivation of the of the infinite dot product is based on Matthew Bernstein's notes: http://pages.cs.wisc.edu/~matthewb/pages/notes/pdf/svms/RBFKernel.pdf
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