xrnet (version 1.0.1)

plot.tune_xrnet: Plot k-fold cross-validation error grid

Description

Generates plots to visualize the mean cross-validation error. If no external data was used in the model fit, a plot of the cross-validated error with standard error bars is generated for all penalty values. If external data was used in the model fit, a contour plot of the cross-validated errors is created. Error curves can also be generated for a fixed value of the primary penalty on x (p) or the external penalty (pext) when external data is used.

Usage

# S3 method for tune_xrnet
plot(x, p = NULL, pext = NULL, ...)

Value

None

Arguments

x

A tune_xrnet class object

p

(optional) penalty value for x (for generating an error curve across external penalties). Use value "opt" to use the optimal penalty value.

pext

(optional) penalty value for external (for generating an error curve across primary penalties). Use value "opt" to use the optimal penalty value.

...

Additional graphics parameters

Details

The parameter values p and pext can be used to generate profiled error curves by fixing either the penalty on x or the penalty on external to a fixed value. You cannot specify both at the same time as this would only return a single point.

Examples

## load example data
data(GaussianExample)

## 5-fold cross validation
cv_xrnet <- tune_xrnet(
  x = x_linear,
  y = y_linear,
  external = ext_linear,
  family = "gaussian",
  control = xrnet_control(tolerance = 1e-6)
)

## contour plot of cross-validated error
plot(cv_xrnet)

## error curve of external penalties at optimal penalty value
plot(cv_xrnet, p = "opt")