Another (lazy) approach is to simply use the useful library
install.packages('useful') library(useful)
Example -
wineUrl <- 'http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data' wine <- read.table(wineUrl, header=F, sep=',') wine_kmeans <- wine[, which(names(wine) != "Cultivar")] wine_cluster <- kmeans(x=wine_kmeans , centers=3) plot(wine_cluster, data=wine_kmeans)

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