plot.as_data: Plot

In ASML: Algorithm Portfolio Selection with Machine Learning

Plot

Description

For an object of class as_data, function that makes several plots, including the following: a boxplot, a ranking plot and comparisons between the different options.

Usage

## S3 method for class 'as_data'
plot(
  x,
  labels = NULL,
  test = TRUE,
  predictions = NULL,
  by_families = FALSE,
  stacked = TRUE,
  legend = TRUE,
  color_list = NULL,
  ml_color = NULL,
  path = NULL,
  ...
)

Arguments

x	object of class as_data.
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.
stacked	boolean to choose between bar plot and stacked bar plot.
legend	boolean to activate or deactivate the legend in the plot.
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.
path	path where plots will be saved. If NULL they won't be saved.
...	other parameters.

Value

A list with boxplot, ranking, fig_comp, optml_fig_comp and optmlall_fig_comp plots.

Examples

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

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