Package website: release | dev
Meta-package for installing and using core mlr3 packages.
This package simplifies installing and loading packages from the mlr3 ecosystem. Instead of attaching extension packages directly, this package re-exports commonly used functions for data analysis and provides a lightweight interface to core mlr3 ecosystem functionality.
# From CRAN:
install.packages("mlr3verse")
# From GitHub:
pak::pak("mlr-org/mlr3verse")Functions and objects from the following packages are imported by this meta-package:
| Name | Title | URL |
|---|---|---|
| mlr3 | Machine Learning in R - Next Generation | https://mlr3.mlr-org.com |
| mlr3cluster | Unsupervised Clustering | https://mlr3cluster.mlr-org.com |
| mlr3data | Additional data sets and tasks | https://mlr3data.mlr-org.com |
| mlr3filters | Filter Based Feature Selection | https://mlr3filters.mlr-org.com |
| mlr3fselect | Wrapper Based Feature Selection | https://mlr3fselect.mlr-org.com |
| mlr3learners | Recommended Learners | https://mlr3learners.mlr-org.com |
| mlr3pipelines | Preprocessing Operators and Pipelines | https://mlr3pipelines.mlr-org.com |
| mlr3torch | Deep Learning | https://mlr3torch.mlr-org.com |
| mlr3tuning | Hyperparameter Tuning | https://mlr3tuning.mlr-org.com |
| mlr3tuningspaces | Collection of Hyperparameter Tuning Spaces | https://mlr3tuningspaces.mlr-org.com |
| mlr3viz | Visualizations | https://mlr3viz.mlr-org.com |
| paradox | Parameter Spaces | https://paradox.mlr-org.com |
After loading mlr3verse, you are ready to work on most
regression, classification, clustering and survival tasks:
library("mlr3verse")For more detailed information about loaded packages, call
mlr3verse_info():
mlr3verse_info()You can install additional packages with:
install.packages("mlr3verse", dependencies = TRUE)| Name | Title | URL |
|---|---|---|
| miesmuschel | Mixed Integer Evolution Strategies | |
| mlr3batchmark | Batch Experiments | https://mlr3batchmark.mlr-org.com |
| mlr3benchmark | Analysis and Visualization of Benchmark Experiments | https://mlr3benchmark.mlr-org.com |
| mlr3db | Database Backend | https://mlr3db.mlr-org.com |
| mlr3fairness | Fairness Auditing and Debiasing | https://mlr3fairness.mlr-org.com |
| mlr3fda | Functional Data Analysis | https://mlr3fda.mlr-org.com |
| mlr3forecast | Time Series Forecasting | https://mlr3forecast.mlr-org.com |
| mlr3oml | OpenML Integration | https://mlr3oml.mlr-org.com |
| mlr3proba | Probabilistic Supervised Learning | https://mlr3proba.mlr-org.com |
| mlr3spatial | Spatial Data Analysis | https://mlr3spatial.mlr-org.com |
| mlr3spatiotempcv | Spatiotemporal Resampling Methods | https://mlr3spatiotempcv.mlr-org.com |
| mlr3summary | Model and Learner Summaries | https://mlr3summary.mlr-org.com |
| mlr3extralearners | Extra Learners | https://mlr3extralearners.mlr-org.com |
| rush | Decentralized and Distributed Computing | https://rush.mlr-org.com |
