[ VIGRA Homepage | Function Index | Class Index | Namespaces | File List | Main Page ]
#include <vigra/random_forest/rf_visitors.hxx>
Public Member Functions | |
template<class RF , class PR , class SM , class ST > | |
void | after_tree_ip_impl (RF &rf, PR &pr, SM &sm, ST &st, int index) |
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_end (RF &rf, PR &pr) |
Public Attributes | |
MultiArray< 2, double > | variable_importance_ |
calculate variable importance while learning.
void visit_after_split | ( | Tree & | tree, |
Split & | split, | ||
Region & | parent, | ||
Region & | leftChild, | ||
Region & | rightChild, | ||
Feature_t & | features, | ||
Label_t & | labels | ||
) |
calculates impurity decrease based variable importance after every split.
Reimplemented from VisitorBase.
void after_tree_ip_impl | ( | RF & | rf, |
PR & | pr, | ||
SM & | sm, | ||
ST & | st, | ||
int | index | ||
) |
compute permutation based var imp. (Only an Array of size oob_sample_count x 1 is created.
void visit_after_tree | ( | RF & | rf, |
PR & | pr, | ||
SM & | sm, | ||
ST & | st, | ||
int | index | ||
) |
calculate permutation based impurity after every tree has been learned default behaviour is that this happens out of place. If you have very big data sets and want to avoid copying of data set the in_place_ flag to true.
Reimplemented from VisitorBase.
void visit_at_end | ( | RF & | rf, |
PR & | pr | ||
) |
Normalise variable importance after the number of trees is known.
MultiArray<2, double> variable_importance_ |
This Array has the same entries as the R - random forest variable importance
© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) |
html generated using doxygen and Python
|