Definition at line 51 of file DecisionTreeNode.h.
Public Member Functions  
DTNodeTrainingInfo ()  
DTNodeTrainingInfo (const DTNodeTrainingInfo &n)  
Public Attributes  
Double_t  fAlpha 
critical alpha for this node More...  
Double_t  fCC 
debug variable for cost complexity pruning .. More...  
Double_t  fG 
minimum alpha in subtree rooted at this node More...  
Double_t  fNB 
sum of weights of background events from the pruning sample in this node More...  
Float_t  fNBkgEvents 
sum of weights of backgr event in the node More...  
Float_t  fNBkgEvents_unboosted 
sum of backgr event in the node More...  
Float_t  fNBkgEvents_unweighted 
sum of backgr event in the node More...  
Float_t  fNEvents 
number of events in that entered the node (during training) More...  
Float_t  fNEvents_unboosted 
number of events in that entered the node (during training) More...  
Float_t  fNEvents_unweighted 
number of events in that entered the node (during training) More...  
Double_t  fNodeR 
node resubstitution estimate, R(t) More...  
Double_t  fNS 
ditto for the signal events More...  
Float_t  fNSigEvents 
sum of weights of signal event in the node More...  
Float_t  fNSigEvents_unboosted 
sum of signal event in the node More...  
Float_t  fNSigEvents_unweighted 
sum of signal event in the node More...  
Int_t  fNTerminal 
number of terminal nodes in subtree rooted at this node More...  
std::vector< Float_t >  fSampleMax 
the maxima for each ivar of the sample on the node during training More...  
std::vector< Float_t >  fSampleMin 
the minima for each ivar of the sample on the node during training More...  
Float_t  fSeparationGain 
measure of "purity", separation, or information gained BY this nodes selection More...  
Float_t  fSeparationIndex 
measure of "purity" (separation between S and B) AT this node More...  
Double_t  fSubTreeR 
R(T) = Sum(R(t) : t in ~T) More...  
Float_t  fSumTarget 
sum of weight*target used for the calculation of the variance (regression) More...  
Float_t  fSumTarget2 
sum of weight*target^2 used for the calculation of the variance (regression) More...  
#include <TMVA/DecisionTreeNode.h>

inline 
Definition at line 54 of file DecisionTreeNode.h.

inline 
Definition at line 96 of file DecisionTreeNode.h.
Double_t TMVA::DTNodeTrainingInfo::fAlpha 
critical alpha for this node
Definition at line 74 of file DecisionTreeNode.h.
Double_t TMVA::DTNodeTrainingInfo::fCC 
debug variable for cost complexity pruning ..
Definition at line 81 of file DecisionTreeNode.h.
Double_t TMVA::DTNodeTrainingInfo::fG 
minimum alpha in subtree rooted at this node
Definition at line 75 of file DecisionTreeNode.h.
Double_t TMVA::DTNodeTrainingInfo::fNB 
sum of weights of background events from the pruning sample in this node
Definition at line 77 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNBkgEvents 
sum of weights of backgr event in the node
Definition at line 84 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNBkgEvents_unboosted 
sum of backgr event in the node
Definition at line 90 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNBkgEvents_unweighted 
sum of backgr event in the node
Definition at line 87 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNEvents 
number of events in that entered the node (during training)
Definition at line 85 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNEvents_unboosted 
number of events in that entered the node (during training)
Definition at line 91 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNEvents_unweighted 
number of events in that entered the node (during training)
Definition at line 88 of file DecisionTreeNode.h.
Double_t TMVA::DTNodeTrainingInfo::fNodeR 
node resubstitution estimate, R(t)
Definition at line 72 of file DecisionTreeNode.h.
Double_t TMVA::DTNodeTrainingInfo::fNS 
ditto for the signal events
Definition at line 78 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNSigEvents 
sum of weights of signal event in the node
Definition at line 83 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNSigEvents_unboosted 
sum of signal event in the node
Definition at line 89 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fNSigEvents_unweighted 
sum of signal event in the node
Definition at line 86 of file DecisionTreeNode.h.
Int_t TMVA::DTNodeTrainingInfo::fNTerminal 
number of terminal nodes in subtree rooted at this node
Definition at line 76 of file DecisionTreeNode.h.
std::vector< Float_t > TMVA::DTNodeTrainingInfo::fSampleMax 
the maxima for each ivar of the sample on the node during training
Definition at line 71 of file DecisionTreeNode.h.
std::vector< Float_t > TMVA::DTNodeTrainingInfo::fSampleMin 
the minima for each ivar of the sample on the node during training
Definition at line 70 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fSeparationGain 
measure of "purity", separation, or information gained BY this nodes selection
Definition at line 93 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fSeparationIndex 
measure of "purity" (separation between S and B) AT this node
Definition at line 92 of file DecisionTreeNode.h.
Double_t TMVA::DTNodeTrainingInfo::fSubTreeR 
Definition at line 73 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fSumTarget 
sum of weight*target used for the calculation of the variance (regression)
Definition at line 79 of file DecisionTreeNode.h.
Float_t TMVA::DTNodeTrainingInfo::fSumTarget2 
sum of weight*target^2 used for the calculation of the variance (regression)
Definition at line 80 of file DecisionTreeNode.h.