Plot for Regression Learners — autoplot.LearnerRegr • mlr3viz

Visualizations for mlr3::LearnerRegr. The argument type controls what kind of plot is drawn. Possible choices are:

"prediction" (default): Decision boundary of the learner and the true class labels.

Usage

# S3 method for class 'LearnerRegr'
autoplot(
  object,
  type = "prediction",
  task,
  grid_points = 100L,
  expand_range = 0,
  theme = theme_minimal(),
  ...
)

Arguments

object: (mlr3::LearnerRegr).
type: (character(1)):
Type of the plot. See description.
task: (mlr3::Task)
Train task.
grid_points: (integer(1))
Number of grid points per feature dimension.
expand_range: (numeric(1))
Expand the range of the grid.
theme: (ggplot2::theme())
The ggplot2::theme_minimal() is applied by default to all plots.
...: (ignored).

Value

ggplot2::ggplot().

Examples

# \donttest{
if (requireNamespace("mlr3")) {
library(mlr3)
library(mlr3viz)

task = tsk("mtcars")$select(c("am", "carb"))
learner = lrn("regr.rpart")
learner$train(task)

autoplot(learner, type = "prediction", task)
}

# }