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OOB_PerTreeError Class Reference |
#include <vigra/random_forest/rf_visitors.hxx>
Public Member Functions | |
template<class RF , class PR , class SM , class ST > | |
void | visit_after_tree (RF &rf, PR &pr, SM &sm, ST &, int index) |
template<class RF , class PR > | |
void | visit_at_end (RF &rf, PR &) |
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 &) |
Public Attributes | |
double | oobError |
Visitor that calculates the oob error of each individual randomized decision tree.
After training a tree, all those samples that are OOB for this particular tree are put down the tree and the error estimated. the per tree oob error is the average of the individual error estimates. (oobError = average error of one randomized tree) Note: This is Not the OOB - Error estimate suggested by Breiman (See OOB_Error visitor)
void visit_after_tree | ( | RF & | rf, |
PR & | pr, | ||
SM & | sm, | ||
ST & | , | ||
int | index | ||
) |
does the basic calculation per tree
void visit_at_end | ( | RF & | rf, |
PR & | |||
) |
Does the normalisation
double oobError |
Average error of one randomized decision tree
© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) |
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