mlr_tuners_async_random_search | R Documentation |
Subclass for asynchronous random search tuning.
The random points are sampled by paradox::generate_design_random()
.
This Tuner can be instantiated with the associated sugar function tnr()
:
tnr("async_random_search")
mlr3tuning::Tuner
-> mlr3tuning::TunerAsync
-> mlr3tuning::TunerAsyncFromOptimizerAsync
-> TunerAsyncRandomSearch
new()
Creates a new instance of this R6 class.
TunerAsyncRandomSearch$new()
clone()
The objects of this class are cloneable with this method.
TunerAsyncRandomSearch$clone(deep = FALSE)
deep
Whether to make a deep clone.
Bergstra J, Bengio Y (2012). “Random Search for Hyper-Parameter Optimization.” Journal of Machine Learning Research, 13(10), 281–305. https://jmlr.csail.mit.edu/papers/v13/bergstra12a.html.
Other TunerAsync:
mlr_tuners_async_design_points
,
mlr_tuners_async_grid_search
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