Feature Selection with Asynchronous Random Search

Feature selection using Asynchronous Random Search Algorithm.

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.

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.

See also

Other FSelectorAsync: mlr_fselectors_async_design_points, mlr_fselectors_async_exhaustive_search

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.