pub trait DTrees_SplitTraitConst {
    fn as_raw_DTrees_Split(&self) -> *const c_void;

    fn var_idx(&self) -> i32 { ... }
    fn inversed(&self) -> bool { ... }
    fn quality(&self) -> f32 { ... }
    fn next(&self) -> i32 { ... }
    fn c(&self) -> f32 { ... }
    fn subset_ofs(&self) -> i32 { ... }
}
Expand description

The class represents split in a decision tree.

Required Methods

Provided Methods

Index of variable on which the split is created.

If true, then the inverse split rule is used (i.e. left and right branches are exchanged in the rule expressions below).

The split quality, a positive number. It is used to choose the best split.

Index of the next split in the list of splits for the node

< The threshold value in case of split on an ordered variable. The rule is:

if var_value < c
  then next_node <- left
  else next_node <- right

< Offset of the bitset used by the split on a categorical variable. The rule is:

if bitset[var_value] == 1
   then next_node <- left
   else next_node <- right

Implementors