wine

These data are the results of a chemical analysis of wines grown in the same region in
Italy but derived from three different cultivars. The analysis determined the quantities
of 13 constituents found in each of the three types of wines.
All 13 attributes are continuous. Distribution of classes: class 1 59x, class 2 71x,
class 3 48x.

datasets

An implementation of the HHCART-G algorithm as described in the
paper - Wickramarachchi C, Robertson B, Reale M, Price C, Brown J (2019). 'A
reflected feature space for CART.' Australian & New Zealand Journal of Statistics,
61, 380<e2><80><93>391. <doi:10.1111/anzs.12275>.

Phil Davies

hhcartr

HHCART(G) - A Reflected Feature Space for CART

wine function

A data frame with 178 rows and 13 variables:<dl class="dl-horizontal">
 <dt>Alcohol</dt><dd></dd>
 <dt>Malic acid</dt><dd></dd>
 <dt>Ash</dt><dd></dd>
 <dt>Alcalinity of ash</dt><dd></dd>
 <dt>Magnesium</dt><dd></dd>
 <dt>Total phenols</dt><dd></dd>
 <dt>Flavanoids</dt><dd></dd>
 <dt>Nonflavanoid phenols</dt><dd></dd>
 <dt>Proanthocyanins</dt><dd></dd>
 <dt>Color intensity</dt><dd></dd>
 <dt>Hue</dt><dd></dd>
 <dt>OD280/OD315 of diluted wines</dt><dd></dd>
 <dt>Proline</dt><dd></dd>
</dl>

Format

Wine recognition data. — wine

A data frame with 178 rows and 13 variables:<dl class='dl-horizontal'>
 <dt>Alcohol</dt><dd></dd>
 <dt>Malic acid</dt><dd></dd>
 <dt>Ash</dt><dd></dd>
 <dt>Alcalinity of ash</dt><dd></dd>
 <dt>Magnesium</dt><dd></dd>
 <dt>Total phenols</dt><dd></dd>
 <dt>Flavanoids</dt><dd></dd>
 <dt>Nonflavanoid phenols</dt><dd></dd>
 <dt>Proanthocyanins</dt><dd></dd>
 <dt>Color intensity</dt><dd></dd>
 <dt>Hue</dt><dd></dd>
 <dt>OD280/OD315 of diluted wines</dt><dd></dd>
 <dt>Proline</dt><dd></dd>
</dl>

wine: Wine recognition data.

Description

Usage

Arguments

Format