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: [ Ссылка ]
Cross Validation: [ Ссылка ]
The Polynomial Kernel: [ Ссылка ]
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: [ Ссылка ]
2) The derivation of the of the infinite dot product is based on Matthew Bernstein's notes: [ Ссылка ]
For a complete index of all the StatQuest videos, check out:
[ Ссылка ]
If you'd like to support StatQuest, please consider...
Buying The StatQuest Illustrated Guide to Machine Learning!!!
PDF - [ Ссылка ]
Paperback - [ Ссылка ]
Kindle eBook - [ Ссылка ]
Patreon: [ Ссылка ]
...or...
YouTube Membership: [ Ссылка ]
...a cool StatQuest t-shirt or sweatshirt:
[ Ссылка ]
...buying one or two of my songs (or go large and get a whole album!)
[ Ссылка ]
...or just donating to StatQuest!
[ Ссылка ]
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
[ Ссылка ]
#statquest #SVM #RBF
