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OOB_Error [Machine Learning] |
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#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 &st, int index) |
template<class RF, class PR> | |
void | visit_at_end (RF &rf, PR &pr) |
Public Attributes | |
double | oob_breiman |
Using normal bagged sampling each sample is OOB for approx. 33% of trees The error rate obtained as such therefore corresponds to crossvalidation rate obtained using a ensemble containing 33% of the trees.
© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) |
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