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precrec::autoplot()
(eg show_cb) when plotting BenchmarkResult and
ResampleResult objects, using type =
roc or prc.type in autoplots now
gives hints of which ones to use.EnsembleFSResult.autoplot to use the
active_measure field.mlr3inferr).LearnerSurvCoxPH.EnsembleFSResult object."prediction" plots for classification and
regression learners."incumbent" plot for
OptimInstanceSingleCrit.binwidth argument to histogram plots."performance" plot always connected the maximum
performance values. Now the minimum values are connected when the
measure is minimized.theme option to autoplot() functions
to supply a ggplot2::theme(). The default is
ggplot2::theme_minimal().theme_mlr3().geom_
functions via .... This behavior was not consistent across
the autoplot() functions.PredictionClassif.LearnerClustHclust.TuningInstanceSingleCrit from package
mlr3tuning.BenchmarkResult
(#63, #65).PredictionClust
(#67).PredictionSurv.glmnet via
ggfortify."holdout"
(#54).TaskDens (#57).autoplot.*() functions now also have a generic S3
plot() sibling (#51).mlr3cluster.BenchmarkResult.mlr3 >= 0.6.0.TaskDens and TaskSurv from
package mlr3proba.PredictionRegr (#23)autoplot.BenchmarkResult(): Support for learners with
identical IDs (#19)plot_learner_prediction() (#47)ResampleResult. Additionally, the helper function
plot_learner_prediction() first performs a
resample() and then plots the result.PredictionRegr.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.