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"we gotta use our mystery mouse catools called context clues and move on."

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split = sample.split(dataset$y, SplitRatio()) training_set = subset(dataset, split ==TRUE) test_set = subset(dataset, split ==FALSE) y is your independent variable of course and you also must have caTools installed.

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After removing unnecessary casts, and some optimisation by @BrodieGaslam, the pure #RStats GIF writing code is now faster than the caTools package! Still heaps slower than #Rcpp version! coolbutuseless.github.io/201…

For K-means I usually use caTools, but have you tried computing the WSS dataframe first to its own object and then plot it afterwards? If plots are big in memory, usually R(Studio) takes a while to show them.