For numerical predictors, data with values of the variable less than
or equal to the splitting point go to the left daughter node.

For categorical predictors, the splitting point is represented by an
integer, whose binary expansion gives the identities of the categories
that goes to left or right. For example, if a predictor has four
categories, and the split point is 13. The binary expansion of 13 is
(1, 0, 1, 1) (because \(13 = 1*2^0 + 0*2^1 + 1*2^2 + 1*2^3\)), so cases with
categories 1, 3, or 4 in this predictor get sent to the left, and the rest
to the right.