SLOPE (version 0.5.1)

plot.TrainedSLOPE: Plot results from cross-validation

Description

Plot results from cross-validation

Usage

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

Value

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

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

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")