Visualizations for mlr3::PredictionClassif.
The argument type
controls what kind of plot is drawn.
Possible choices are:
"stacked"
(default): Stacked barplot of true and estimated class labels."roc"
: ROC curve (1 - specificity on x, sensitivity on y). Requires package precrec."prc"
: Precision recall curve. Requires package precrec."threshold"
: Systematically varies the threshold of the mlr3::PredictionClassif object and plots the resulting performance as returned bymeasure
.
Usage
# S3 method for PredictionClassif
autoplot(
object,
type = "stacked",
measure = NULL,
theme = theme_minimal(),
...
)
Arguments
- object
- type
(character(1)):
Type of the plot. See description.- measure
(mlr3::Measure)
Performance measure to use.- theme
(
ggplot2::theme()
)
Theggplot2::theme_minimal()
is applied by default to all plots.- ...
(ignored).
References
Saito T, Rehmsmeier M (2017). “Precrec: fast and accurate precision-recall and ROC curve calculations in R.” Bioinformatics, 33(1), 145-147. doi:10.1093/bioinformatics/btw570 .