Returns all the splits

splits = model.getSplits()

Output

• splits Struct-array with the following fields:
  • varIdx Index of variable on which the split is created.
  • inversed If true, then the inverse split rule is used (i.e. left and right branches are exchanged in the rule expressions below).
  • quality The split quality, a positive number. It is used to choose the best split. (It is also used to compute variable importance).
  • next Index of the next split in the list of splits for the node (surrogate splits).
  • c The threshold value in case of split on an ordered variable. The rule is: if var_value < c, next_node = left; else next_node = right; end
  • subsetOfs Offset of the bitset used by the split on a categorical variable. The rule is: if bitset(var_value) == 1, next_node = left; else next_node = right; end

all the split indices are zero-based indices in the returned vector.