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Meta-package for installing and using core mlr3 packages.

mlr3verse

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():

Additional packages can be installed 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 Visualisation 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
mlr3oml OpenML Integration https://mlr3oml.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
mlr3torch Deep Learning https://mlr3torch.mlr-org.com
rush Decentralized and Distributed Computing https://rush.mlr-org.com