cv_krr: Choose best lambda via cross-validation.
In TimothyKBook/krr: Kernel Ridge Regression
Description
Usage
Arguments
Value
Description
A very crude method to find the optimal lambda for a krr (kernel ridge
regression) model.
Usage
1
cv_krr(x, y, lambda_index)
Arguments
x
Quantitative explanatory variables (vector, matrix, or data.frame).
y
Quantitative response variable.
lambda_index
Vector of lambdas to scan for best model.
Value
Returns best lambda, MSE, and model. Also returns a dataframe of
every lambda_index value and corresponding MSE.
TimothyKBook/krr documentation built on May 9, 2019, 4:48 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value
Description
A very crude method to find the optimal lambda for a krr (kernel ridge regression) model.
Usage
1 | cv_krr(x, y, lambda_index)
|
Arguments
x |
Quantitative explanatory variables (vector, matrix, or data.frame). |
y |
Quantitative response variable. |
lambda_index |
Vector of lambdas to scan for best model. |
Value
Returns best lambda, MSE, and model. Also returns a dataframe of every lambda_index value and corresponding MSE.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.