data_partition creates a test/training partition.
data_partition(y, p = 0.5, groups = min(5, length(y)))a vector of outcomes.
the percentage of data that goes to training
for numeric y, the number of breaks in the quantiles
(see below)
A vector of row position integers corresponding to the training data
The random sampling is done within the levels of y when y is a
factor in an attempt to balance the class distributions within the splits.
For numeric y, the sample is split into groups sections based on
percentiles and sampling is done within these subgroups. The number of
percentiles is set via the groups argument.
Also, very small class sizes (<= 3) the classes may not show up in both the training and test data