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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... For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon:   / statquest   ...or... YouTube Membership:    / @statquest   ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statques... ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:   / joshuastarmer   #statquest #SVM #RBF