Trait opencv::ml::DTrees_SplitTrait

pub trait DTrees_SplitTrait: DTrees_SplitTraitConst {
    // Required method
    fn as_raw_mut_DTrees_Split(&mut self) -> *mut c_void;

    // Provided methods
    fn set_var_idx(&mut self, val: i32) { ... }
    fn set_inversed(&mut self, val: bool) { ... }
    fn set_quality(&mut self, val: f32) { ... }
    fn set_next(&mut self, val: i32) { ... }
    fn set_c(&mut self, val: f32) { ... }
    fn set_subset_ofs(&mut self, val: i32) { ... }
}

Mutable methods for crate::ml::DTrees_Split

Required Methods

fn as_raw_mut_DTrees_Split(&mut self) -> *mut c_void

Provided Methods

fn set_var_idx(&mut self, val: i32)

Index of variable on which the split is created.

fn set_inversed(&mut self, val: bool)

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

fn set_quality(&mut self, val: f32)

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

fn set_next(&mut self, val: i32)

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

fn set_c(&mut self, val: f32)

< 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

fn set_subset_ofs(&mut self, val: i32)

< 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

impl DTrees_SplitTrait for DTrees_Split