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Tip revision: c27795bfae1e3309def7b5fa022d60a7ca28b75a authored by Catherine Hurley on 07 January 2019, 19:00 UTC
version 1.3.2
Tip revision: c27795b
\title{Wine recognition data}
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.

\format{This data frame contains the following columns:
 \item{Class:}{There are 3 classes}
 \item{Malic:}{Malic acid}
 \item{Alcalinity:}{Alcalinity of ash}
 \item{Phenols:}{Total phenols}
 \item{Nonflavanoid:}{Nonflavanoid phenols}
 \item{Intensity:}{Color intensity}
 \item{OD280:}{OD280/OD315 of diluted wines}

Forina, M. et al, PARVUS - An Extendible Package for Data
       Exploration, Classification and Correlation. Institute of Pharmaceutical
       and Food Analysis and Technologies, Via Brigata Salerno, 
       16147 Genoa, Italy.
Blake, C.L. and Merz, C.J. (1998), UCI Repository of machine learning databases, \\
\url{}. Irvine, CA: University of California, Department of
Information and Computer Science. 

The database does not list the variable names. These were
located at 
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