Uploaded November 2019 | Updated September 2026, 1 week ago
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: youtu.be/efR1C6CvhmE
Cross Validation: youtu.be/fSytzGwwBVw
The Polynomial Kernel: 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
For a complete index of all the StatQuest videos, check out:
statquest.org/video-index
If you'd like to support StatQuest, please consider...
Patreon: patreon.com/statquest
...or...
YouTube Membership: youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store...
statquest.org/statquest-store
...or just donating to StatQuest!
paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
twitter.com/joshuastarmer
#statquest #SVM #RBF
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: youtu.be/efR1C6CvhmE
Cross Validation: youtu.be/fSytzGwwBVw
The Polynomial Kernel: 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
For a complete index of all the StatQuest videos, check out:
statquest.org/video-index
If you'd like to support StatQuest, please consider...
Patreon: patreon.com/statquest
...or...
YouTube Membership: youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store...
statquest.org/statquest-store
...or just donating to StatQuest!
paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
twitter.com/joshuastarmer
#statquest #SVM #RBF
