mlr3tuning.async_default_configuration

<p>These CallbackAsyncTuning and CallbackBatchTuning evaluate the default hyperparameter values of a learner.</p>

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.

Marc Becker

mlr3tuning

Hyperparameter Optimization for 'mlr3'

Michel Lang

Jakob Richter

Bernd Bischl

Daniel Schalk

mlr3tuning.async_default_configuration function

Default Configuration Callback — mlr3tuning.async_default_configuration

Default Configuration Callback

mlr3tuning.async_default_configuration: Default Configuration Callback

Description

Arguments