| FastKRR-package | Kernel Ridge Regression using the 'RcppArmadillo' Package |
| approx_kernel | Compute low-rank approximations (Nyström, Pivoted Cholesky, RFF) |
| coef.krr | Extract Model Coefficients from a Fitted KRR Model |
| error | Compute Model Error for Kernel Ridge Regression Models |
| error.krr | Compute Model Error for Kernel Ridge Regression Models |
| FastKRR | Kernel Ridge Regression using the 'RcppArmadillo' Package |
| fastkrr | Fit kernel ridge regression using exact or approximate methods |
| krr_reg | Kernel Ridge Regression |
| make_kernel | Kernel matrix construction for given datasets |
| param.krr | Displays hyperparameters of fitted Kernel Ridge Regression models |
| plot.krr | Plot method for fitted Kernel Ridge Regression models |
| predict.krr | Predict responses for new data using fitted KRR model |
| print.approx_kernel | Print method for approximated kernel matrices |
| print.krr | Print method for fitted Kernel Ridge Regression models |
| summary.krr | Summary method for fitted Kernel Ridge Regression models |
| tunable.krr_reg | Expose tunable parameters for '"krr_reg"' |