View source: R/PredictionRegr.R
autoplot.PredictionRegr | R Documentation |
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).
## S3 method for class 'PredictionRegr' autoplot(object, type = "xy", ...)
object |
(mlr3::PredictionRegr). |
type |
(character(1)): |
... |
( |
ggplot2::ggplot()
object.
The theme_mlr3()
and viridis color maps are applied by default to all
autoplot()
methods. To change this behavior set
options(mlr3.theme = FALSE)
.
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")
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