CorrelationVisitor Class Reference

Inheritance diagram for CorrelationVisitor:

Additional Inherited Members
Public Member Functions inherited from VisitorBase
double	return_val ()

template<class Tree , class Split , class Region , class Feature_t , class Label_t >
void	visit_after_split (Tree &tree, Split &split, Region &parent, Region &leftChild, Region &rightChild, Feature_t &features, Label_t &labels)

template<class RF , class PR , class SM , class ST >
void	visit_after_tree (RF &rf, PR &pr, SM &sm, ST &st, int index)

template<class RF , class PR >
void	visit_at_beginning (RF const &rf, PR const &pr)

template<class RF , class PR >
void	visit_at_end (RF const &rf, PR const &pr)

template<class TR , class IntT , class TopT , class Feat >
void	visit_external_node (TR &tr, IntT index, TopT node_t, Feat &features)

template<class TR , class IntT , class TopT , class Feat >
void	visit_internal_node (TR &, IntT, TopT, Feat &)

Detailed Description

Computes Correlation/Similarity Matrix of features while learning random forest.

Member Data Documentation

MultiArray<2, double> gini_missc

gini_missc(ii, jj) describes how well variable jj can describe a partition created on variable ii(when variable ii was chosen)

MultiArray<2, double> noise

additional noise features.

MultiArray<2, double> corr_noise

how well can a noise column describe a partition created on variable ii.

MultiArray<2, double> similarity

Similarity Matrix

(numberOfFeatures + 1) by (number Of Features + 1) Matrix gini_missc

MultiArray<2, double> distance

Distance Matrix 1-similarity

ArrayVector<int> numChoices

How often was variable ii chosen

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