Summarize TrainedSLOPE Model

Produces a summary of a trained SLOPE model from cross-validation, including information about the optimal parameters and performance metrics.

Usage

# S3 method for class 'TrainedSLOPE'
summary(object, ...)

Arguments

object

an object of class 'TrainedSLOPE', typically from a call to cvSLOPE() or trainSLOPE()

...

other arguments (currently ignored)

Value

An object of class 'summary_TrainedSLOPE' with the following components:

call

the call that produced the model

measure

the performance measure(s) used

optima

optimal parameter values and corresponding performance

n_folds

number of cross-validation folds

n_repeats

number of cross-validation repeats

n_models

total number of models evaluated

See also

cvSLOPE(), trainSLOPE(), print.summary_TrainedSLOPE()

Other model-tuning: cvSLOPE(), plot.TrainedSLOPE(), refit(), trainSLOPE()

Examples

tune <- cvSLOPE(
  subset(mtcars, select = c("mpg", "drat", "wt")),
  mtcars$hp,
  q = c(0.1, 0.2),
  n_folds = 5
)
summary(tune)
#> 
#> Call:
#> cvSLOPE(x = subset(mtcars, select = c("mpg", "drat", "wt")), 
#>     y = mtcars$hp, q = c(0.1, 0.2), n_folds = 5) 
#> 
#> Cross-validation:
#>   Folds: 5 
#>   Repeats: 1 
#>   Models evaluated: 133 
#> 
#> Performance measure: Mean Squared Error 
#> 
#> Optimal parameters:
#>    q gamma alpha measure mean  se  lo   hi
#>  0.1     0   2.9     mse 2060 534 575 3540