mlr3tuning and mlr3hyperband

Hyperband is a specialized hyperparameter optimization algorithm that can be used as a backend tuning strategy within mlr3tuning's broader optimization framework.

mlr3tuning
51
Established
mlr3hyperband
50
Established
Maintenance 13/25
Adoption 8/25
Maturity 16/25
Community 14/25
Maintenance 13/25
Adoption 6/25
Maturity 16/25
Community 15/25
Stars: 59
Forks: 8
Downloads:
Commits (30d): 0
Language: R
License: LGPL-3.0
Stars: 18
Forks: 5
Downloads:
Commits (30d): 0
Language: R
License: LGPL-3.0
No Package No Dependents
No Package No Dependents

About mlr3tuning

mlr-org/mlr3tuning

Hyperparameter optimization package of the mlr3 ecosystem

This tool helps data scientists and machine learning engineers automatically find the best settings for their predictive models. You provide your machine learning model and the range of settings you'd like to explore, and the tool outputs the optimal settings that yield the best model performance. It's designed for anyone building and evaluating machine learning models in R.

machine-learning model-optimization predictive-modeling data-science statistical-modeling

About mlr3hyperband

mlr-org/mlr3hyperband

Successive Halving and Hyperband in the mlr3 ecosystem

This project helps data scientists efficiently find the best settings (hyperparameters) for their machine learning models. You provide your model and the range of settings to test, and it outputs the optimized settings that lead to better model performance. It's designed for data scientists and machine learning practitioners who build and refine predictive models.

machine-learning-optimization predictive-modeling model-tuning data-science-workflow

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