mlr_tuners_async_random_search: Hyperparameter Tuning with Asynchronous Random Search

In mlr3tuning: Hyperparameter Optimization for 'mlr3'

Hyperparameter Tuning with Asynchronous Random Search

Description

Subclass for asynchronous random search tuning.

Details

The random points are sampled by paradox::generate_design_random().

Dictionary

This Tuner can be instantiated with the associated sugar function tnr():

tnr("async_random_search")

Super classes

mlr3tuning::Tuner -> mlr3tuning::TunerAsync -> mlr3tuning::TunerAsyncFromOptimizerAsync -> TunerAsyncRandomSearch

Methods

Public methods

• TunerAsyncRandomSearch$new()

• TunerAsyncRandomSearch$clone()

Inherited methods

• mlr3tuning::Tuner$format()
• mlr3tuning::Tuner$help()
• mlr3tuning::Tuner$print()
• mlr3tuning::TunerAsyncFromOptimizerAsync$optimize()

---

Method new()

Creates a new instance of this R6 class.

Usage

TunerAsyncRandomSearch$new()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

TunerAsyncRandomSearch$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Source

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.

See Also

Other TunerAsync: mlr_tuners_async_design_points, mlr_tuners_async_grid_search

mlr3tuning documentation built on June 8, 2025, 10:41 a.m.