TunerAsync: Class for Asynchronous Tuning Algorithms

In mlr3tuning: Hyperparameter Optimization for 'mlr3'

Class for Asynchronous Tuning Algorithms

Description

The TunerAsync implements the asynchronous optimization algorithm.

Details

TunerAsync is an abstract base class that implements the base functionality each asynchronous tuner must provide.

Resources

There are several sections about hyperparameter optimization in the mlr3book.

• An overview of all tuners can be found on our website.

• Learn more about tuners.

The gallery features a collection of case studies and demos about optimization.

• Use the Hyperband optimizer with different budget parameters.

Super class

mlr3tuning::Tuner -> TunerAsync

Methods

Public methods

• TunerAsync$optimize()

• TunerAsync$clone()

Inherited methods

• mlr3tuning::Tuner$format()
• mlr3tuning::Tuner$help()
• mlr3tuning::Tuner$initialize()
• mlr3tuning::Tuner$print()

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Method optimize()

Performs the tuning on a TuningInstanceAsyncSingleCrit or TuningInstanceAsyncMultiCrit until termination. The single evaluations will be written into the ArchiveAsyncTuning that resides in the TuningInstanceAsyncSingleCrit/TuningInstanceAsyncMultiCrit. The result will be written into the instance object.

Usage

TunerAsync$optimize(inst)

Arguments

inst

(TuningInstanceAsyncSingleCrit | TuningInstanceAsyncMultiCrit).

Returns

data.table::data.table()

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Method clone()

The objects of this class are cloneable with this method.

Usage

TunerAsync$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

mlr3tuning documentation built on Oct. 27, 2024, 9:06 a.m.