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Meta-package for installing and using core mlr3 packages.

mlr3verse

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Overview

This package is intended to simplify both installation and loading of packages from the mlr3 ecosystem. Instead of depending on the extension packages, functions required for data analysis are re-exported, providing a thin view on the most important functionality of the mlr3 ecosystem.

Installation

# From CRAN:
install.packages("mlr3verse")

# From Github:
remotes::install_github("mlr-org/mlr3verse")

Batteries included

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
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

By loading the mlr3verse package, you are all set to deal with most regression, classification, cluster and survival tasks:

library("mlr3verse")
#> Loading required package: mlr3

If you want to get more detailed information about the loaded packages, you can call mlr3verse_info():

mlr3verse_info()

More extension packages are available on CRAN/GitHub, and may be included in this meta package in the future.

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.