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details RFVisitorBase Class Reference VIGRA

Base class from which all random forest visitors derive. More...

#include <vigra/random_forest_3/random_forest_visitors.hxx>

Inheritance diagram for RFVisitorBase:
OOBError RFStopVisiting VariableImportance

Public Member Functions

void activate ()
 Activate the visitor.
 
void deactivate ()
 Deactivate the visitor.
 
bool is_active () const
 Return whether the visitor is active or not.
 
template<typename TREE , typename FEATURES , typename LABELS , typename WEIGHTS , typename SCORER , typename ITER >
void visit_after_split (TREE &, FEATURES &, LABELS &, WEIGHTS &, SCORER &, ITER, ITER, ITER)
 Do something after the split was made.
 
template<typename VISITORS , typename RF , typename FEATURES , typename LABELS >
void visit_after_training (VISITORS &, RF &, const FEATURES &, const LABELS &)
 Do something after all trees have been learned. More...
 
template<typename RF , typename FEATURES , typename LABELS , typename WEIGHTS >
void visit_after_tree (RF &, FEATURES &, LABELS &, WEIGHTS &)
 Do something after a tree has been learned.
 
void visit_before_training ()
 Do something before training starts.
 
template<typename TREE , typename FEATURES , typename LABELS , typename WEIGHTS >
void visit_before_tree (TREE &, FEATURES &, LABELS &, WEIGHTS &)
 Do something before a tree has been learned. More...
 

Detailed Description

Base class from which all random forest visitors derive.

Due to the parallel training, we cannot simply use a single visitor for all trees. Instead, each tree gets a copy of the original visitor.

The random forest training with visitors looks as follows:

Member Function Documentation

void visit_after_training ( VISITORS &  ,
RF &  ,
const FEATURES &  ,
const LABELS &   
)

Do something after all trees have been learned.

Parameters
vvector with pointers to the visitor copies
rfthe trained random forest
void visit_before_tree ( TREE &  ,
FEATURES &  ,
LABELS &  ,
WEIGHTS &   
)

Do something before a tree has been learned.

Parameters
weightsthe actual instance weights (after bootstrap sampling and class weights)

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

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de)
Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

html generated using doxygen and Python
vigra 1.11.0 (Fri May 19 2017)