When performing cross-validation on a dataset, it often becomes necessary to split the data into training and test sets that are balanced for a certain binary outcome. This function implements such a balanced split.
A factor that should be balnced between the two subsets.
A number between 0 and 1 indicating the fraction of the dataset to be used for training.
Stuff should go here
Returns a logical vector with length equal to the length of
fac. TRUE values designate samples selected for the training
Kevin R. Coombes <email@example.com>
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