Support Vector Machines Part 3: The Radial (RBF) Kernel (Part 3 of 3)
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: • Support Vector Machines Part 1 (of 3)...
Cross Validation: • Machine Learning Fundamentals: Cross ...
The Polynomial Kernel: • Support Vector Machines Part 2: The P...
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/garet...
2) The derivation of the of the infinite dot product is based on Matthew Bernstein's notes: http://pages.cs.wisc.edu/~matthewb/pa...
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