mlr_fselectors_async_random_search: Feature Selection with Asynchronous Random Search

In mlr-org/mlr3fselect: Feature Selection for 'mlr3'

Feature Selection with Asynchronous Random Search

Description

Feature selection using Asynchronous Random Search Algorithm.

Details

The feature sets are randomly drawn. The sets are evaluated asynchronously. The algorithm uses bbotk::OptimizerAsyncRandomSearch for optimization.

Dictionary

This FSelector can be instantiated with the associated sugar function fs():

fs("async_random_search")

Control Parameters

max_features

integer(1)
Maximum number of features. By default, number of features in mlr3::Task.

Super classes

mlr3fselect::FSelector -> mlr3fselect::FSelectorAsync -> FSelectorAsyncRandomSearch

Methods

Public methods

• FSelectorAsyncRandomSearch$new()

• FSelectorAsyncRandomSearch$clone()

Inherited methods

• mlr3fselect::FSelector$format()
• mlr3fselect::FSelector$help()
• mlr3fselect::FSelector$print()
• mlr3fselect::FSelectorAsync$optimize()

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Method new()

Creates a new instance of this R6 class.

Usage

FSelectorAsyncRandomSearch$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

FSelectorAsyncRandomSearch$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 FSelectorAsync: mlr_fselectors_async_design_points, mlr_fselectors_async_exhaustive_search

mlr-org/mlr3fselect documentation built on July 5, 2025, 3:22 a.m.