The class represents split in a decision tree. More...

#include "ml.hpp"

Collaboration diagram for cv::ml::DTrees::Split:

Public Attributes
float	c
	The threshold value in case of split on an ordered variable. More...

bool	inversed
	If true, then the inverse split rule is used (i.e. More...

int	next
	Index of the next split in the list of splits for the node. More...

float	quality
	The split quality, a positive number. More...

int	subsetOfs
	Offset of the bitset used by the split on a categorical variable. More...

int	varIdx
	Index of variable on which the split is created. More...

Detailed Description

The class represents split in a decision tree.

Constructor & Destructor Documentation

cv::ml::DTrees::Split::Split ( )

float cv::ml::DTrees::Split::c

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

bool cv::ml::DTrees::Split::inversed

If true, then the inverse split rule is used (i.e.

left and right branches are exchanged in the rule expressions below).

int cv::ml::DTrees::Split::next

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

float cv::ml::DTrees::Split::quality

The split quality, a positive number.

It is used to choose the best split.

int cv::ml::DTrees::Split::subsetOfs

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

int cv::ml::DTrees::Split::varIdx

Index of variable on which the split is created.

The documentation for this class was generated from the following file: