autoplot.LearnerClassifRpart: Plots for Rpart Learners

In mlr3viz: Visualizations for 'mlr3'

Plots for Rpart Learners

Description

Visualizations for mlr3::LearnerClassifRpart. 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.

• "ggparty": Visualizes the tree using the package ggparty.

Usage

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

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

Arguments

object	(mlr3::LearnerClassifRpart | mlr3::LearnerRegrRpart).
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

if (requireNamespace("mlr3")) {
  library(mlr3)
  library(mlr3viz)

  # classification
  task = tsk("iris")
  learner = lrn("classif.rpart", keep_model = TRUE)
  learner$train(task)
  autoplot(learner, type = "ggparty")

  # regression
  task = tsk("mtcars")
  learner = lrn("regr.rpart", keep_model = TRUE)
  learner$train(task)
  autoplot(learner, type = "ggparty")
}

mlr3viz documentation built on July 1, 2024, 5:06 p.m.