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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
Browse package contents
Package details |
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| Author | Marc Becker [cre, aut] (<https://orcid.org/0000-0002-8115-0400>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Daniel Schalk [aut] (<https://orcid.org/0000-0003-0950-1947>) |
| Maintainer | Marc Becker <marcbecker@posteo.de> |
| License | LGPL-3 |
| Version | 1.1.0 |
| URL | https://mlr3tuning.mlr-org.com https://github.com/mlr-org/mlr3tuning |
| Package repository | View on CRAN |
| Installation |
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