autoplot.PredictionRegr: Plot for PredictionRegr

In mlr3viz: Visualizations for 'mlr3'

Plot for PredictionRegr

Description

Generates plots for mlr3::PredictionRegr, depending on argument type:

• "xy" (default): Scatterplot of "true" response vs. "predicted" response. By default a linear model is fitted via geom_smooth(method = "lm") to visualize the trend between x and y (by default colored blue).

  • In addition geom_abline() with slope = 1 is added to the plot.

  • Note that geom_smooth() and geom_abline() may overlap, depending on the given data.

• "histogram": Histogram of residuals: r = y - y.hat.

• "residual": Plot of the residuals, with the response y.hat on the "x" and the residuals on the "y" axis.

  • By default a linear model is fitted via geom_smooth(method = "lm") to visualize the trend between x and y (by default colored blue).

Usage

## S3 method for class 'PredictionRegr'
autoplot(object, type = "xy", ...)

Arguments

object	(mlr3::PredictionRegr).
type	(character(1)): Type of the plot. See description.
...	(any): Additional arguments, passed down to the respective geom.

Value

ggplot2::ggplot() object.

Theme

The theme_mlr3() and viridis color maps are applied by default to all autoplot() methods. To change this behavior set options(mlr3.theme = FALSE).

Examples

library(mlr3)
library(mlr3viz)

task = tsk("boston_housing")
learner = lrn("regr.rpart")
object = learner$train(task)$predict(task)

head(fortify(object))
autoplot(object)
autoplot(object, type = "histogram", binwidth = 1)
autoplot(object, type = "residual")

mlr3viz documentation built on May 25, 2022, 5:06 p.m.