The `boxplot_training` function creates a box plot that displays the performance of a set of configurations on the training instances. Performance data is obtained from the evaluations performed by irace during the execution process. This implies that the number of evaluations can differ between configurations.

boxplot_training(
  irace_results,
  iteration = NULL,
  id_configurations = NULL,
  rpd = TRUE,
  file_name = NULL
)

Arguments

irace_results

The data generated when loading the Rdata file created by irace

iteration

Numeric, iteration number that should be included in the plot (example: iteration = 5) When no iteration and no id_condigurations are provided, the iterations is assumed to be the last one performed by irace.

The performance data is obtained from the evaluations performed by irace during the execution process. This implies that the number of evaluations can differ between configurations due to the elimination process applied by irace. This plot, consequently, does not provide a complete compaarison of two configurations, for a fair comparison use the test data plot.

id_configurations

Numeric vector, configurations ids whose performance should be included in the plot. If no ids are provided, the configurations ids are set as the elite configuration ids of the selected iteration (last iteration by default) (example: id_configurations = c(20,50,100,300,500,600,700)).

rpd

Logical (default TRUE), TRUE to plot performance as the relative percentage deviation to best results per instance, FALSE to plot raw performance.

file_name

String, file name to save plot (example: "~/patch/example/file_name.png")

Value

box plot

Examples

boxplot_training(iraceResults)
boxplot_training(iraceResults, rpd = FALSE)
boxplot_training(iraceResults, iteration = 5)
boxplot_training(iraceResults, id_configurations = c(20, 50, 100, 300, 500, 600, 700))