selection-class

This class contains the result of feature selection algorithms.

Contains functions to simplify the use of data mining methods (classification, regression, clustering, etc.), for students and beginners in R programming. Various R packages are used and wrappers are built around the main functions, to standardize the use of data mining methods (input/output): it brings a certain loss of flexibility, but also a gain of simplicity. The package name came from the French "Fouille de Données en Master 2 Informatique Décisionnelle".

Alexandre Blansch<c3><a9>

fdm2id

Data Mining and R Programming for Beginners

Alexandre Blansché

selection-class function

<dl>
<dt><code>selection</code></dt>
<dd>A vector of integers indicating the selected features.</dd></dl>
<dt><code>unieval</code></dt>
<dd>The evaluation of the features (univariate).</dd>
<dt><code>multieval</code></dt>
<dd>The evaluation of the selected features (multivariate).</dd>
<dt><code>algorithm</code></dt>
<dd>The algorithm used to select features.</dd>
<dt><code>univariate</code></dt>
<dd>The evaluation criterion (univariate).</dd>
<dt><code>nbfeatures</code></dt>
<dd>The number of features to be kept.</dd>
<dt><code>threshold</code></dt>
<dd>The threshold to decide whether a feature is kept or not..</dd>
<dt><code>multivariate</code></dt>
<dd>The evaluation criterion (multivariate).</dd>
<dt><code>dataset</code></dt>
<dd>The dataset described by the selected features only.</dd>
<dt><code>model</code></dt>
<dd>The classification model.</dd>

Slots

Feature selection — selection-class

<dl>
<dt><code>selection</code></dt>
<dd>A vector of integers indicating the selected features.</dd>


<dt><code>unieval</code></dt>
<dd>The evaluation of the features (univariate).</dd>


<dt><code>multieval</code></dt>
<dd>The evaluation of the selected features (multivariate).</dd>


<dt><code>algorithm</code></dt>
<dd>The algorithm used to select features.</dd>


<dt><code>univariate</code></dt>
<dd>The evaluation criterion (univariate).</dd>


<dt><code>nbfeatures</code></dt>
<dd>The number of features to be kept.</dd>


<dt><code>threshold</code></dt>
<dd>The threshold to decide whether a feature is kept or not..</dd>


<dt><code>multivariate</code></dt>
<dd>The evaluation criterion (multivariate).</dd>


<dt><code>dataset</code></dt>
<dd>The dataset described by the selected features only.</dd>


<dt><code>model</code></dt>
<dd>The classification model.</dd>


</dl>

selection-class: Feature selection

Description

Arguments

Slots

See Also