wine

Data from the machine learning repository.
A chemical analysis
of 178 Italian wines from three different cultivars yielded 13 measurements.
This dataset is often used to test and compare the performance of various
classification algorithms.

datasets

Orders panels in scatterplot matrices and parallel coordinate
displays by some merit index. Package contains various indices of merit,
ordering functions, and enhanced versions of pairs and parcoord which
color panels according to their merit level.

Catherine Hurley

gclus

Clustering Graphics

wine function

This data frame contains the following columns:<dl class="dl-horizontal">
 <dt>Class:</dt><dd>There are 3 classes</dd>
 <dt>Alcohol:</dt><dd>Alcohol</dd>
 <dt>Malic:</dt><dd>Malic acid</dd>
 <dt>Ash:</dt><dd>Ash</dd>
 <dt>Alcalinity:</dt><dd>Alcalinity of ash</dd>
 <dt>Magnesium:</dt><dd>Magnesium</dd>
 <dt>Phenols:</dt><dd>Total phenols</dd>
 <dt>Flavanoids:</dt><dd>Flavanoids</dd>
 <dt>Nonflavanoid:</dt><dd>Nonflavanoid phenols</dd>
 <dt>Proanthocyanins:</dt><dd>Proanthocyanins</dd>
 <dt>Intensity:</dt><dd>Color intensity</dd>
 <dt>Hue:</dt><dd>Hue</dd>
 <dt>OD280:</dt><dd>OD280/OD315 of diluted wines</dd>
 <dt>Proline:</dt><dd>Proline</dd>
</dl>

Format

Wine recognition data — wine

This data frame contains the following columns:<dl class='dl-horizontal'>
 <dt>Class:</dt><dd>There are 3 classes</dd>
 <dt>Alcohol:</dt><dd>Alcohol</dd>
 <dt>Malic:</dt><dd>Malic acid</dd>
 <dt>Ash:</dt><dd>Ash</dd>
 <dt>Alcalinity:</dt><dd>Alcalinity of ash</dd>
 <dt>Magnesium:</dt><dd>Magnesium</dd>
 <dt>Phenols:</dt><dd>Total phenols</dd>
 <dt>Flavanoids:</dt><dd>Flavanoids</dd>
 <dt>Nonflavanoid:</dt><dd>Nonflavanoid phenols</dd>
 <dt>Proanthocyanins:</dt><dd>Proanthocyanins</dd>
 <dt>Intensity:</dt><dd>Color intensity</dd>
 <dt>Hue:</dt><dd>Hue</dd>
 <dt>OD280:</dt><dd>OD280/OD315 of diluted wines</dd>
 <dt>Proline:</dt><dd>Proline</dd>
</dl>

wine: Wine recognition data

Description

Usage

Arguments

Format

References