Whisky

Data frame with five features of 35 whisky brands:<dl>
 <dt>price</dt>
<dd>in Frace Francs</dd> <dt>malt</dt>
<dd>proportion in percentage</dd> <dt>type</dt>
<dd>by malt proportion: low, medium, pure</dd> <dt>aging</dt>
<dd>in years</dd> <dt>taste</dt>
<dd>mean score of a taste panel</dd> 
</dl>

datasets

Some functions of 'ade4' and 'stats' are combined in order to obtain
a partition of the rows of a data table, with columns representing
variables of scales: quantitative, qualitative or frequency.
First, a principal axes method is performed and then, a combination
of Ward agglomerative hierarchical classification and K-means is
performed, using some of the first coordinates obtained from the
previous principal axes method.
In order to permit different weights of the elements to be clustered,
the function 'kmeansW', programmed in C++, is included.
It is a modification of 'kmeans'. Some graphical functions include
the option: 'gg=FALSE'.  When 'gg=TRUE', they  use the 'ggplot2'
and 'ggrepel' packages to avoid  the super-position of the labels.

Campo Pardo

FactoClass

Combination of Factorial Methods and Cluster Analysis

Whisky function

Data frame with five features of 35 whisky brands:<dl>
 <dt>price</dt>
<dd>in Frace Francs</dd>

 <dt>malt</dt>
<dd>proportion in percentage</dd>

 <dt>type</dt>
<dd>by malt proportion: low, medium, pure</dd>

 <dt>aging</dt>
<dd>in years</dd>

 <dt>taste</dt>
<dd>mean score of a taste panel</dd>

 
</dl>

Whisky: Whisky example

Description

Usage

Arguments