Mlr3hyperband: Hyperband for 'Mlr3'

MCML Authors

Marc Becker

→ Group Bernd Bischl
 Statistical Learning and Data Science

Julia Moosbauer

Dr.

* Former Member

→ Group Bernd Bischl
 Statistical Learning and Data Science

Bernd Bischl

Prof. Dr.

Director

Statistical Learning and Data Science

Abstract

mlr3hyperband adds the optimization algorithms Successive Halving (Jamieson and Talwalkar 2016) and Hyperband (Li et al. 2018) to the mlr3 ecosystem. The implementation in mlr3hyperband features improved scheduling and parallelizes the evaluation of configurations. The package includes tuners for hyperparameter optimization in mlr3tuning and optimizers for black-box optimization in bbotk.

manual BGR+21

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SW Package

Jan. 2021

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Authors

M. Becker • S. Gruber • J. Richter • J. Moosbauer • B. Bischl

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Links

URL GitHub

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Research Area

 A1 | Statistical Foundations & Explainability