Performs Correspondence Analysis (CA) including supplementary row and/or column points.

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

CA function

<dl><dt>d</dt>
<dd>A data frame or a table with n rows and p columns, i.e. a contingency table.</dd>
<dt>ncp</dt>
<dd>The number of dimensions kept in the results. All of them, by default: a table of
I active rows by J active columns carries <code>min (I, J) - 1</code> of them, the first dimension
of a contingency table being its margins, which hold no association.</dd>
<dt>row.sup</dt>
<dd>A vector indicating the indexes of the supplementary rows.</dd>
<dt>col.sup</dt>
<dd>A vector indicating the indexes of the supplementary columns.</dd>
<dt>quanti.sup</dt>
<dd>A vector indicating the indexes of the supplementary continuous variables.</dd>
<dt>quali.sup</dt>
<dd>A vector indicating the indexes of the categorical supplementary variables.</dd>
<dt>row.w</dt>
<dd>An optional row weights (by default, a vector of 1 for uniform row weights); the weights are given only for the active individuals.</dd></dl>

Arguments

Correspondence Analysis (CA) — CA

<dl>

<dt>d</dt>
<dd>A data frame or a table with n rows and p columns, i.e. a contingency table.</dd>


<dt>ncp</dt>
<dd>The number of dimensions kept in the results. All of them, by default: a table of
I active rows by J active columns carries <code>min (I, J) - 1</code> of them, the first dimension
of a contingency table being its margins, which hold no association.</dd>


<dt>row.sup</dt>
<dd>A vector indicating the indexes of the supplementary rows.</dd>


<dt>col.sup</dt>
<dd>A vector indicating the indexes of the supplementary columns.</dd>


<dt>quanti.sup</dt>
<dd>A vector indicating the indexes of the supplementary continuous variables.</dd>


<dt>quali.sup</dt>
<dd>A vector indicating the indexes of the categorical supplementary variables.</dd>


<dt>row.w</dt>
<dd>An optional row weights (by default, a vector of 1 for uniform row weights); the weights are given only for the active individuals.</dd>

</dl>

CA: Correspondence Analysis (CA)

Description

Usage

Value

Arguments

See Also

Examples