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".

Data Mining and R Programming for Beginners

package-ubuntu-20.04-r-4.0.5#cran#fdm2id-0.9.5

<p>Apply the keiser rule to determine the appropriate number of PCA axes.
</p>

<table summary="R argblock"><tr valign="top">
<td><code>pca</code></td>
<td>
<p>The PCA result (object of class <code>factorial-class</code>).</p>
</td>
</tr></table>

<p><code><a href="PCA.html">PCA</a></code>, <code><a href="factorial-class.html">factorial-class</a></code>
</p>

require (datasets)
data (iris)
pca = PCA (iris, quali.sup = 5)
keiser (pca)

package-ubuntu-20.04-r-4.0.5#cran#fdm2id-0.9.5#docs#keiser

keiser

Description

Usage

Arguments

See Also

Examples

fdm2id

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