Kernel Ridge Regression using 'RcppArmadillo'


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Documentation for package ‘FastKRR’ version 0.1.2

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FastKRR-package Kernel Ridge Regression using the 'RcppArmadillo' Package
approx_kernel Compute low-rank approximations(Nyström, Pivoted Cholesky, RFF)
coef.krr Coef method for fitted Kernel Ridge Regression models
error Compute Model Error (Generic)
error.default Compute Model Error (Generic)
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 K construction for given datasets
param Extract/print hyperparameters of fitted models
param.default Extract/print hyperparameters of fitted models
param.krr Param method for fitted Kernel Ridge Regression models
plot.krr Plot method for fitted Kernel Ridge Regression (KRR) models
predict.krr Predict responses for new data using fitted KRR model
print.approx_kernel Print method for approximated kernel matrices
print.kernel_matrix Print method for 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"'