SummaryFunction

<p>Abstract used as template to define customized metrics to
compute model performance during train.</p>

misc

Provides a novel framework to able to automatically develop and deploy
an accurate Multiple Classifier System based on the feature-clustering
distribution achieved from an input dataset. 'D2MCS' was developed focused on
four main aspects: (i) the ability to determine an effective method to
evaluate the independence of features, (ii) the identification of the
optimal number of feature clusters, (iii) the training and tuning of ML
models and (iv) the execution of voting schemes to combine the outputs of
each classifier comprising the Multiple  Classifier System.

Miguel Ferreiro-D<c3><ad>az

D2MCS

Data Driving Multiple Classifier System

David Ruano-Ordás

Miguel Ferreiro-Díaz

José Ramón Méndez

University of Vigo 

SummaryFunction function


<div class="section" id="public-methods">
<h3>Public methods</h3><p></p><p><ul>
<li><p><a href="/link/SummaryFunction%24new()?package=D2MCS&version=1.0.1" data-mini-rdoc="D2MCS::SummaryFunction$new()"><code>SummaryFunction$new()</code></a></p></li>
<li><p><a href="/link/SummaryFunction%24execute()?package=D2MCS&version=1.0.1" data-mini-rdoc="D2MCS::SummaryFunction$execute()"><code>SummaryFunction$execute()</code></a></p></li>
<li><p><a href="/link/SummaryFunction%24getMeasures()?package=D2MCS&version=1.0.1" data-mini-rdoc="D2MCS::SummaryFunction$getMeasures()"><code>SummaryFunction$getMeasures()</code></a></p></li>
<li><p><a href="/link/SummaryFunction%24clone()?package=D2MCS&version=1.0.1" data-mini-rdoc="D2MCS::SummaryFunction$clone()"><code>SummaryFunction$clone()</code></a></p></li>
</ul></p><p></p></div><p><hr>
<a id="method-SummaryFunction-new"></a></p><div class="section" id="method-new-">
<h3>Method <code>new()</code></h3>
<p>The function carries out the initialization of parameters
during runtime.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>SummaryFunction$new(measures)</code></pre><p></p></div><p></p>
</div><p></p><p><div class="section" id="arguments">
<h4>Arguments</h4>
<p><div class="arguments"></div></p><dl>
<dt><code>measures</code></dt>
<dd><p>A <a href="/link/character?package=D2MCS&version=1.0.1" data-mini-rdoc="D2MCS::character">character</a> vector with the measures used.</p></dd></dl></div></p><p>
</p><p></p>
<p></p><p></p><p><hr>
<a id="method-SummaryFunction-execute"></a></p><div class="section" id="method-execute-">
<h3>Method <code>execute()</code></h3>
<p>Abstract function used to implement the performance
calculator method. To guarantee a proper operation, this method is
automatically invoked by <code>D2MCS</code> framework.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>SummaryFunction$execute()</code></pre><p></p></div><p></p>
</div><p></p><p>
</p><p><hr>
<a id="method-SummaryFunction-getMeasures"></a></p><div class="section" id="method-getmeasures-">
<h3>Method <code>getMeasures()</code></h3>
<p>The function obtains the measures used to compute the
performance across resamples.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>SummaryFunction$getMeasures()</code></pre><p></p></div><p></p>
</div><p></p><p><div class="section" id="returns">
<h4>Returns</h4>
<p>A <a href="/link/character?package=D2MCS&version=1.0.1" data-mini-rdoc="D2MCS::character">character</a> vector of <a href="/link/NULL?package=D2MCS&version=1.0.1" data-mini-rdoc="D2MCS::NULL">NULL</a> if measures are not
defined.</p>
</div></p><p></p><p><hr>
<a id="method-SummaryFunction-clone"></a></p><div class="section" id="method-clone-">
<h3>Method <code>clone()</code></h3>
<p>The objects of this class are cloneable with this method.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>SummaryFunction$clone(deep = FALSE)</code></pre><p></p></div><p></p>
</div><p></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></dl></div></p><p>
</p><p></p>
<p></p><p>
</p>

Methods

Abstract class to computing performance across resamples. — SummaryFunction


<div class='section' id='public-methods'>
<h3>Public methods</h3>

<ul>
<li><p><a href='#method-SummaryFunction-new'><code>SummaryFunction$new()</code></a></p></li>
<li><p><a href='#method-SummaryFunction-execute'><code>SummaryFunction$execute()</code></a></p></li>
<li><p><a href='#method-SummaryFunction-getMeasures'><code>SummaryFunction$getMeasures()</code></a></p></li>
<li><p><a href='#method-SummaryFunction-clone'><code>SummaryFunction$clone()</code></a></p></li>
</ul>

</div><p><hr>
<a id="method-SummaryFunction-new"></a></p><div class='section' id='method-new-'>
<h3>Method <code>new()</code></h3>
<p>The function carries out the initialization of parameters
during runtime.</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>SummaryFunction$new(measures)</code></pre><p></div></p>
</div>

<div class='section' id='arguments'>
<h4>Arguments</h4>
<p><div class="arguments"></p><dl>
<dt><code>measures</code></dt>
<dd><p>A <a href='https://rdrr.io/r/base/character.html'>character</a> vector with the measures used.</p></dd>


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

</div><p><hr>
<a id="method-SummaryFunction-execute"></a></p><div class='section' id='method-execute-'>
<h3>Method <code>execute()</code></h3>
<p>Abstract function used to implement the performance
calculator method. To guarantee a proper operation, this method is
automatically invoked by <code>D2MCS</code> framework.</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>SummaryFunction$execute()</code></pre><p></div></p>
</div>


</div><p><hr>
<a id="method-SummaryFunction-getMeasures"></a></p><div class='section' id='method-getmeasures-'>
<h3>Method <code>getMeasures()</code></h3>
<p>The function obtains the measures used to compute the
performance across resamples.</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>SummaryFunction$getMeasures()</code></pre><p></div></p>
</div>

<div class='section' id='returns'>
<h4>Returns</h4>
<p>A <a href='https://rdrr.io/r/base/character.html'>character</a> vector of <a href='https://rdrr.io/r/base/NULL.html'>NULL</a> if measures are not
defined.</p>
</div>

</div><p><hr>
<a id="method-SummaryFunction-clone"></a></p><div class='section' id='method-clone-'>
<h3>Method <code>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>SummaryFunction$clone(deep = FALSE)</code></pre><p></div></p>
</div>

<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>


SummaryFunction: Abstract class to computing performance across resamples.

Description

Arguments

Methods

Public methods

Method `new()`

Usage

Arguments

Method `execute()`

Usage

Method `getMeasures()`

Usage

Returns

Method `clone()`

Usage

Arguments

Details

See Also

Description

Arguments

Methods

Public methods

Method new()

Usage

Arguments

Method execute()

Usage

Method getMeasures()

Usage

Returns

Method clone()

Usage

Arguments

Details

See Also

Method `new()`

Method `execute()`

Method `getMeasures()`

Method `clone()`