This is a comprehensive tutorial of Support Vector Machines in R, for classification and regression.
- Linearly separated examples
- Non seperable examples
- Non linear data - and the kernel trick
- Cross-validation: choosing the right cost and kernel paremeters
- SVR
(sorry for some problems with the caret package, Binder's R is still at 3.4.4)