![]() |
ROOT
6.06/09
Reference Guide
|
Definition at line 59 of file ExpectedErrorPruneTool.h.
Public Member Functions | |
| ExpectedErrorPruneTool () | |
| virtual | ~ExpectedErrorPruneTool () |
| virtual PruningInfo * | CalculatePruningInfo (DecisionTree *dt, const IPruneTool::EventSample *testEvents=NULL, Bool_t isAutomatic=kFALSE) |
| void | SetPruneStrengthIncrement (Double_t dalpha) |
Public Member Functions inherited from TMVA::IPruneTool | |
| IPruneTool () | |
| virtual | ~IPruneTool () |
| void | SetPruneStrength (Double_t alpha) |
| Double_t | GetPruneStrength () const |
| void | SetAutomatic () |
| Bool_t | IsAutomatic () const |
Private Member Functions | |
| void | FindListOfNodes (DecisionTreeNode *node) |
| recursive pruning of nodes using the Expected Error Pruning (EEP) More... | |
| Double_t | GetNodeError (DecisionTreeNode *node) const |
| Calculate an UPPER limit on the error made by the classification done by this node. More... | |
| Double_t | GetSubTreeError (DecisionTreeNode *node) const |
| calculate the expected statistical error on the subtree below "node" which is used in the expected error pruning More... | |
| Int_t | CountNodes (DecisionTreeNode *node, Int_t icount=0) |
| MsgLogger & | Log () const |
Private Attributes | |
| Double_t | fDeltaPruneStrength |
| Double_t | fNodePurityLimit |
| the stepsize for optimizing the pruning strength parameter More... | |
| std::vector< DecisionTreeNode * > | fPruneSequence |
| the purity limit for labelling a terminal node as signal More... | |
| MsgLogger * | fLogger |
| the (optimal) prune sequence More... | |
Additional Inherited Members | |
Public Types inherited from TMVA::IPruneTool | |
| typedef std::vector< const Event * > | EventSample |
Protected Attributes inherited from TMVA::IPruneTool | |
| Double_t | fPruneStrength |
| Double_t | S |
| regularization parameter in pruning More... | |
| Double_t | B |
#include <TMVA/ExpectedErrorPruneTool.h>
Inheritance diagram for TMVA::ExpectedErrorPruneTool:
Collaboration diagram for TMVA::ExpectedErrorPruneTool:| TMVA::ExpectedErrorPruneTool::ExpectedErrorPruneTool | ( | ) |
Definition at line 34 of file ExpectedErrorPruneTool.cxx.
|
virtual |
Definition at line 43 of file ExpectedErrorPruneTool.cxx.
|
virtual |
Implements TMVA::IPruneTool.
Definition at line 51 of file ExpectedErrorPruneTool.cxx.
|
inlineprivate |
Definition at line 86 of file ExpectedErrorPruneTool.h.
|
private |
recursive pruning of nodes using the Expected Error Pruning (EEP)
Definition at line 147 of file ExpectedErrorPruneTool.cxx.
|
private |
Calculate an UPPER limit on the error made by the classification done by this node.
If the S/S+B of the node is f, then according to the training sample, the error rate (fraction of misclassified events by this node) is (1-f) Now f has a statistical error according to the binomial distribution hence the error on f can be estimated (same error as the binomial error for efficency calculations ( sigma = sqrt(eff(1-eff)/nEvts ) )
Definition at line 190 of file ExpectedErrorPruneTool.cxx.
|
private |
calculate the expected statistical error on the subtree below "node" which is used in the expected error pruning
Definition at line 165 of file ExpectedErrorPruneTool.cxx.
|
inlineprivate |
Definition at line 83 of file ExpectedErrorPruneTool.h.
Definition at line 70 of file ExpectedErrorPruneTool.h.
|
private |
Definition at line 78 of file ExpectedErrorPruneTool.h.
Referenced by SetPruneStrengthIncrement().
|
mutableprivate |
the (optimal) prune sequence
Definition at line 82 of file ExpectedErrorPruneTool.h.
Referenced by Log().
|
private |
the stepsize for optimizing the pruning strength parameter
Definition at line 79 of file ExpectedErrorPruneTool.h.
|
private |
the purity limit for labelling a terminal node as signal
Definition at line 80 of file ExpectedErrorPruneTool.h.