if (!file.exists('wine.data'))
{
UCI <- "ftp://ftp.ics.uci.edu/pub"
REPOS <- "ml-repos/machine-learning-databases"
wine.url <- sprintf("%s/%s/wine/wine.data", UCI, REPOS)
download.file(wine.url, "wine.data")
wine <- read.csv("wine.data", header=F) 
colnames(wine) <- c('Type', 'Alcohol', 'Malic', 'Ash', 
                    'Alcalinity', 'Magnesium', 'Phenols', 
                    'Flavanoids', 'Nonflavanoids',
                    'Proanthocyanins', 'Color', 'Hue', 
                    'Dilution', 'Proline')
wine$Type <- as.factor(wine$Type)
write.table(wine, "wine.csv", sep=",", row.names=FALSE)
save(wine, file="wine.Rdata", compress=TRUE)
}