boxplots.as_data: Boxplots

In ASML: Algorithm Portfolio Selection with Machine Learning

Boxplots

Description

Represents a boxplot for each of the algorithms to compare their performance according to the response variable (KPI). When available, it also includes a box plot for the "ML" algorithm generated from the predictions.

Usage

## S3 method for class 'as_data'
boxplots(
  data_object,
  main = "Boxplot Comparison",
  labels = NULL,
  test = TRUE,
  predictions = NULL,
  by_families = FALSE,
  color_list = NULL,
  ml_color = NULL,
  ordered_option_names = NULL,
  xlab = "Strategy",
  ylab = "KPI",
  ...
)

Arguments

data_object	object of class as_data.
main	an overall title for the plot.
labels	character vector with the labels for each of the algorithms. If NULL, the y names of the data_object names will be used.
test	flag that indicates whether the function should use test data or training data.
predictions	a data frame with the predicted KPI for each algorithm (columns) and for each instance (rows). If NULL, the plot won't include a ML column.
by_families	boolean indicating whether the function should represent data by families or not. The family information must be included in the data_object parameter.
color_list	list with the colors for the plots. If NULL, or insufficient number of colors, the colors will be generated automatically.
ml_color	color por the ML boxplot. If NULL, it will be generated automatically.
ordered_option_names	vector with the name of the columns of data_object y variable in the correct order.
xlab	a label for the x axis.
ylab	a label for the y axis.
...	other parameters.

Value

A ggplot object representing the boxplots of instance-normalized KPI for each algorithm across instances.

Examples

data(branchingsmall)
data <- partition_and_normalize(branchingsmall$x, branchingsmall$y)
training <- AStrain(data, method = "glm")
predict_test <- ASpredict(training, newdata = data$x.test)
boxplots(data, predictions = predict_test)

ASML documentation built on April 3, 2025, 8:47 p.m.