The training set (description), as a <code>data.frame</code>.

train

Class labels of the training set (<code>vector</code> or <code>factor</code>).

labels

If true, the function returns paramters instead of a classification model.

tune

This function builds a classification model using Logistic Regression.

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

KNN function

<dl><dt>train</dt>
<dd>The training set (description), as a <code>data.frame</code>.</dd>
<dt>labels</dt>
<dd>Class labels of the training set (<code>vector</code> or <code>factor</code>).</dd>
<dt>k</dt>
<dd>The k parameter.</dd>
<dt>tune</dt>
<dd>If true, the function returns paramters instead of a classification model.</dd>
<dt>...</dt>
<dd>Other parameters.</dd></dl>

Arguments

Classification using k-NN — KNN

<dl>

<dt>train</dt>
<dd>The training set (description), as a <code>data.frame</code>.</dd>


<dt>labels</dt>
<dd>Class labels of the training set (<code>vector</code> or <code>factor</code>).</dd>


<dt>k</dt>
<dd>The k parameter.</dd>


<dt>tune</dt>
<dd>If true, the function returns paramters instead of a classification model.</dd>


<dt>...</dt>
<dd>Other parameters.</dd>

</dl>

KNN: Classification using k-NN

Description

Usage

Value

Arguments

See Also

Examples