[−][src]Trait opencv::ml::prelude::DTrees_SplitTrait

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

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

    pub fn var_idx(&self) -> i32 { ... }

    pub fn set_var_idx(&mut self, val: i32) { ... }

    pub fn inversed(&self) -> bool { ... }

    pub fn set_inversed(&mut self, val: bool) { ... }

    pub fn quality(&self) -> f32 { ... }

    pub fn set_quality(&mut self, val: f32) { ... }

    pub fn next(&self) -> i32 { ... }

    pub fn set_next(&mut self, val: i32) { ... }

    pub fn c(&self) -> f32 { ... }

    pub fn set_c(&mut self, val: f32) { ... }

    pub fn subset_ofs(&self) -> i32 { ... }

    pub fn set_subset_ofs(&mut self, val: i32) { ... }
}

The class represents split in a decision tree.

Required methods

pub fn as_raw_DTrees_Split(&self) -> *const c_void[src]

pub fn as_raw_mut_DTrees_Split(&mut self) -> *mut c_void[src]

Loading content...

Provided methods

pub fn var_idx(&self) -> i32[src]

Index of variable on which the split is created.

pub fn set_var_idx(&mut self, val: i32)[src]

Index of variable on which the split is created.

pub fn inversed(&self) -> bool[src]

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

pub fn set_inversed(&mut self, val: bool)[src]

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

pub fn quality(&self) -> f32[src]

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

pub fn set_quality(&mut self, val: f32)[src]

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

pub fn next(&self) -> i32[src]

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

pub fn set_next(&mut self, val: i32)[src]

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

pub fn c(&self) -> f32[src]

< 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

pub fn set_c(&mut self, val: f32)[src]

< 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

pub fn subset_ofs(&self) -> i32[src]

< 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

pub fn set_subset_ofs(&mut self, val: i32)[src]

< 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
Loading content...

Implementors

impl DTrees_SplitTrait for DTrees_Split[src]

Loading content...