mlr_tuners_async_random_search

TunerAsyncRandomSearch

<p>Subclass for asynchronous random search tuning.</p>

Hyperparameter optimization package of the 'mlr3' ecosystem.
It features highly configurable search spaces via the 'paradox'
package and finds optimal hyperparameter configurations for any 'mlr3'
learner.  'mlr3tuning' works with several optimization algorithms e.g.
Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo')
and Hyperband (in 'mlr3hyperband'). Moreover, it can automatically
optimize learners and estimate the performance of optimized models
with nested resampling.

Marc Becker

mlr3tuning

Hyperparameter Optimization for 'mlr3'

Michel Lang

Jakob Richter

Bernd Bischl

Daniel Schalk

mlr_tuners_async_random_search function

<p></p><p></p><p>This Tuner can be instantiated with the associated sugar function <code>tnr()</code>:</p>
<p><div class="sourceCode"></div></p><pre><code>tnr("async_random_search")
</code></pre><p></p>

Dictionary

<p><code>Tuner</code> -&gt; <code>TunerAsync</code> -&gt; <code>TunerAsyncFromOptimizerAsync</code> -&gt; <code>TunerAsyncRandomSearch</code></p>

Super classes


<div class="section" id="public-methods">
<h3>Public methods</h3>
<p></p><ul>
<li><p><a href="/link/TunerAsyncRandomSearch%24new()?package=mlr3tuning&version=1.6.1" data-mini-rdoc="mlr3tuning::TunerAsyncRandomSearch$new()"><code>TunerAsyncRandomSearch$new()</code></a></p></li>
<li><p><a href="/link/TunerAsyncRandomSearch%24clone()?package=mlr3tuning&version=1.6.1" data-mini-rdoc="mlr3tuning::TunerAsyncRandomSearch$clone()"><code>TunerAsyncRandomSearch$clone()</code></a></p></li>
</ul><p></p><p></p></div><p><details open><summary>Inherited methods</summary>
<ul>
  <li><span class="pkg-link" data-pkg="mlr3tuning" data-topic="Tuner" data-id="format"><a href="/link/Tuner%24format()?package=mlr3tuning&version=1.6.1" data-mini-rdoc="mlr3tuning::Tuner$format()"><code>Tuner$format()</code></a></span></li>
  <li><span class="pkg-link" data-pkg="mlr3tuning" data-topic="Tuner" data-id="help"><a href="/link/Tuner%24help()?package=mlr3tuning&version=1.6.1" data-mini-rdoc="mlr3tuning::Tuner$help()"><code>Tuner$help()</code></a></span></li>
  <li><span class="pkg-link" data-pkg="mlr3tuning" data-topic="Tuner" data-id="print"><a href="/link/Tuner%24print()?package=mlr3tuning&version=1.6.1" data-mini-rdoc="mlr3tuning::Tuner$print()"><code>Tuner$print()</code></a></span></li>
  <li><span class="pkg-link" data-pkg="mlr3tuning" data-topic="TunerAsyncFromOptimizerAsync" data-id="optimize"><a href="/link/TunerAsyncFromOptimizerAsync%24optimize()?package=mlr3tuning&version=1.6.1" data-mini-rdoc="mlr3tuning::TunerAsyncFromOptimizerAsync$optimize()"><code>TunerAsyncFromOptimizerAsync$optimize()</code></a></span></li>
</ul>
</details>
<hr>
<a id="method-TunerAsyncRandomSearch-initialize"></a></p><div class="section" id="tunerasyncrandomsearch-new-">
<h3><code>TunerAsyncRandomSearch$new()</code></h3>
<p>Creates a new instance of this <a href="https://r6.r-lib.org/reference/R6Class.html">R6</a> class.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>TunerAsyncRandomSearch$new()</code></pre><p></p></div><p></p>
</div><p></p><p></p><p></p><p><hr>
<a id="method-TunerAsyncRandomSearch-clone"></a></p><div class="section" id="tunerasyncrandomsearch-clone-">
<h3><code>TunerAsyncRandomSearch$clone()</code></h3>
<p>The objects of this class are cloneable with this method.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>TunerAsyncRandomSearch$clone(deep = FALSE)</code></pre><p></p></div><p></p>
</div><p></p><div class="section" id="arguments">
<h4>Arguments</h4>
<p><div class="arguments"></div></p><dl>
      <dt><code>deep</code></dt>
<dd><p>Whether to make a deep clone.</p></dd><p></p><p>    
</p></dl><p></p></div><p></p>
<p></p><p></p><p></p>

Methods

Hyperparameter Tuning with Asynchronous Random Search — mlr_tuners_async_random_search



<p>This Tuner can be instantiated with the associated sugar function <code>tnr()</code>:</p>
<p><div class="sourceCode"></p><pre><code>tnr("async_random_search")
</code></pre><p></div></p>


<div class='section' id='public-methods'>
<h3>Public methods</h3>
<p></p><ul>
<li><p><a href='#method-TunerAsyncRandomSearch-initialize'><code>TunerAsyncRandomSearch$new()</code></a></p></li>
<li><p><a href='#method-TunerAsyncRandomSearch-clone'><code>TunerAsyncRandomSearch$clone()</code></a></p></li>
</ul>

</div><p><details open><summary>Inherited methods</summary>
<ul>
  <li><span class="pkg-link" data-pkg="mlr3tuning" data-topic="Tuner" data-id="format"><a href='../../mlr3tuning/html/Tuner.html#method-Tuner-format'><code>Tuner$format()</code></a></span></li>
  <li><span class="pkg-link" data-pkg="mlr3tuning" data-topic="Tuner" data-id="help"><a href='../../mlr3tuning/html/Tuner.html#method-Tuner-help'><code>Tuner$help()</code></a></span></li>
  <li><span class="pkg-link" data-pkg="mlr3tuning" data-topic="Tuner" data-id="print"><a href='../../mlr3tuning/html/Tuner.html#method-Tuner-print'><code>Tuner$print()</code></a></span></li>
  <li><span class="pkg-link" data-pkg="mlr3tuning" data-topic="TunerAsyncFromOptimizerAsync" data-id="optimize"><a href='../../mlr3tuning/html/TunerAsyncFromOptimizerAsync.html#method-TunerAsyncFromOptimizerAsync-optimize'><code>TunerAsyncFromOptimizerAsync$optimize()</code></a></span></li>
</ul>
</details>
<hr>
<a id="method-TunerAsyncRandomSearch-initialize"></a></p><div class='section' id='tunerasyncrandomsearch-new-'>
<h3><code>TunerAsyncRandomSearch$new()</code></h3>
<p>Creates a new instance of this <a href='https://r6.r-lib.org/reference/R6Class.html'>R6</a> class.</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>TunerAsyncRandomSearch$new()</code></pre><p></div></p>
</div>

</div>

<p><hr>
<a id="method-TunerAsyncRandomSearch-clone"></a></p><div class='section' id='tunerasyncrandomsearch-clone-'>
<h3><code>TunerAsyncRandomSearch$clone()</code></h3>
<p>The objects of this class are cloneable with this method.</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>TunerAsyncRandomSearch$clone(deep = FALSE)</code></pre><p></div></p>
</div><p></p><div class='section' id='arguments'>
<h4>Arguments</h4>
<p><div class="arguments"></p><dl>
      <dt><code>deep</code></dt>
<dd><p>Whether to make a deep clone.</p></dd>

    
</dl><p></div></p>
</div>

</div>



mlr_tuners_async_random_search: Hyperparameter Tuning with Asynchronous Random Search

Description

Arguments

Dictionary

Super classes

Methods

Public methods

`TunerAsyncRandomSearch$new()`

Usage

`TunerAsyncRandomSearch$clone()`

Usage

Arguments

Details

See Also