mlr-org/mlr3tuning: Hyperparameter Optimization for 'mlr3'

Hyperparameter optimization package of the 'mlr3' ecosystem. It features highly configurable search spaces via the 'paradox' package and finds optimal hyperparameter configurations for any 'mlr3' learner. 'mlr3tuning' works with several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). Moreover, it can automatically optimize learners and estimate the performance of optimized models with nested resampling.

Getting started

Package details

Maintainer
LicenseLGPL-3
Version1.3.0.9000
URL https://mlr3tuning.mlr-org.com https://github.com/mlr-org/mlr3tuning
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("mlr-org/mlr3tuning")
mlr-org/mlr3tuning documentation built on April 14, 2025, 1 a.m.