The class represents split in a decision tree.
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#include "ml.hpp"
The class represents split in a decision tree.
cv::ml::DTrees::Split::Split |
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float cv::ml::DTrees::Split::c |
The threshold value in case of split on an ordered variable. The rule is:
3 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:
1 if bitset[var_value] == 1
3 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: