Package: mlr3viz 0.10.0
Marc Becker
mlr3viz: Visualizations for 'mlr3'
Visualization package of the 'mlr3' ecosystem. It features plots for mlr3 objects such as tasks, learners, predictions, benchmark results, tuning instances and filters via the 'autoplot()' generic of 'ggplot2'. The package draws plots with the 'viridis' color palette and applies the minimal theme. Visualizations include barplots, boxplots, histograms, ROC curves, and Precision-Recall curves.
Authors:
mlr3viz_0.10.0.tar.gz
mlr3viz_0.10.0.zip(r-4.5)mlr3viz_0.10.0.zip(r-4.4)mlr3viz_0.10.0.zip(r-4.3)
mlr3viz_0.10.0.tgz(r-4.4-any)mlr3viz_0.10.0.tgz(r-4.3-any)
mlr3viz_0.10.0.tar.gz(r-4.5-noble)mlr3viz_0.10.0.tar.gz(r-4.4-noble)
mlr3viz_0.10.0.tgz(r-4.4-emscripten)mlr3viz_0.10.0.tgz(r-4.3-emscripten)
mlr3viz.pdf |mlr3viz.html✨
mlr3viz/json (API)
NEWS
| # Install 'mlr3viz' in R: |
| install.packages('mlr3viz', repos = c('https://mlr-org.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mlr-org/mlr3viz/issues
ggplot2mlr3visualizationvisualizations
Last updated 15 days agofrom:39a6677c05 (on v0.10.0). Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 07 2024 |
| R-4.5-win | OK | Nov 07 2024 |
| R-4.5-linux | OK | Nov 07 2024 |
| R-4.4-win | OK | Nov 07 2024 |
| R-4.4-mac | OK | Nov 07 2024 |
| R-4.3-win | OK | Nov 07 2024 |
| R-4.3-mac | OK | Nov 07 2024 |
Exports:as_precrecautoplotfortifyplot_learner_prediction
Dependencies:backportscheckmateclicolorspacedata.tabledigestfansifarverggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmlr3miscmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| mlr3viz: Visualizations for 'mlr3' | mlr3viz-package mlr3viz |
| Convert to 'precrec' Format | as_precrec as_precrec.BenchmarkResult as_precrec.PredictionClassif as_precrec.ResampleResult |
| Plots for Benchmark Results | autoplot.BenchmarkResult |
| Plots for Ensemble Feature Selection Results | autoplot.EnsembleFSResult |
| Plots for Filter Scores | autoplot.Filter |
| Plot for Classification Learners | autoplot.LearnerClassif |
| Plots for GLMNet Learners | autoplot.LearnerClassifCVGlmnet autoplot.LearnerClassifGlmnet autoplot.LearnerRegrCVGlmnet autoplot.LearnerRegrGlmnet |
| Plots for Rpart Learners | autoplot.LearnerClassifRpart autoplot.LearnerRegrRpart |
| Plots for Hierarchical Clustering Learners | autoplot.LearnerClustHierarchical |
| Plot for Regression Learners | autoplot.LearnerRegr |
| Plots for Cox Proportional Hazards Learner | autoplot.LearnerSurvCoxPH |
| Plots for Optimization Instances | autoplot.OptimInstanceBatchSingleCrit |
| Plots for Classification Predictions | autoplot.PredictionClassif |
| Plots for Cluster Predictions | autoplot.PredictionClust |
| Plots for Regression Predictions | autoplot.PredictionRegr |
| Plots for Resample Results | autoplot.ResampleResult |
| Plots for Classification Tasks | autoplot.TaskClassif |
| Plots for Clustering Tasks | autoplot.TaskClust |
| Plots for Regression Tasks | autoplot.TaskRegr |
| Plots for Tuning Instances | autoplot.TuningInstanceBatchSingleCrit |
| Plots for Learner Predictions | plot_learner_prediction |
| Generates a data.table of evenly distributed points. | predict_grid |
