plot.TrainedSLOPE: Plot results from cross-validation

In SLOPE: Sorted L1 Penalized Estimation

Plot results from cross-validation

Description

Plot results from cross-validation

Usage

## S3 method for class 'TrainedSLOPE'
plot(
  x,
  measure = c("auto", "mse", "mae", "deviance", "auc", "misclass"),
  plot_min = TRUE,
  ci_alpha = 0.2,
  ci_border = FALSE,
  ci_col = "salmon",
  ...
)

Arguments

x	an object of class 'TrainedSLOPE', typically from a call to trainSLOPE()
measure	any of the measures used in the call to trainSLOPE(). If measure = "auto" then deviance will be used for binomial and multinomial models, whilst mean-squared error will be used for Gaussian and Poisson models.
plot_min	whether to mark the location of the penalty corresponding to the best prediction score
ci_alpha	alpha (opacity) for fill in confidence limits
ci_border	color (or flag to turn off and on) the border of the confidence limits
ci_col	color for border of confidence limits
...	words

Value

An object of class "ggplot", which will be plotted on the current device unless stored in a variable.

See Also

trainSLOPE()

Other model-tuning: caretSLOPE(), trainSLOPE()

Examples

# Cross-validation for a SLOPE binomial model
set.seed(123)
tune <- trainSLOPE(subset(mtcars, select = c("mpg", "drat", "wt")),
  mtcars$hp,
  q = c(0.1, 0.2),
  number = 10
)
plot(tune, ci_col = "salmon")

SLOPE documentation built on June 10, 2022, 1:05 a.m.