Visualizations for mlr3::PredictionRegr.
The argument `type`

controls what kind of plot is drawn.
Possible choices are:

`"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: \(r = y - \hat{y}\).`"residual"`

: Plot of the residuals, with the response \(\hat{y}\) 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 PredictionRegr
autoplot(object, type = "xy", binwidth = NULL, theme = theme_minimal(), ...)
```

## Arguments

- object
- type
(character(1)):

Type of the plot. See description.- binwidth
(

`integer(1)`

)

Width of the bins for the histogram.- theme
(

`ggplot2::theme()`

)

The`ggplot2::theme_minimal()`

is applied by default to all plots.- ...
(ignored).