assert_batch_tuning_callback

assert_batch_tuning_callbacks

Assertions for CallbackBatchTuning class.

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

assert_batch_tuning_callback function

<dl><dt>callback</dt>
<dd>(CallbackBatchTuning).</dd>
<dt>null_ok</dt>
<dd>(<code>logical(1)</code>) 
If <code>TRUE</code>, <code>NULL</code> is allowed.</dd>
<dt>callbacks</dt>
<dd>(list of CallbackBatchTuning).</dd></dl>

Arguments

Assertions for Callbacks — assert_batch_tuning_callback

<dl>

<dt>callback</dt>
<dd>(CallbackBatchTuning).</dd>


<dt>null_ok</dt>
<dd>(<code>logical(1)</code>) 
If <code>TRUE</code>, <code>NULL</code> is allowed.</dd>


<dt>callbacks</dt>
<dd>(list of CallbackBatchTuning).</dd>

</dl>

assert_batch_tuning_callback: Assertions for Callbacks

Description

Usage

Value

Arguments