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 | |
Double_t | fCC |
debug variable for cost complexity pruning .. | |
Double_t | fG |
minimum alpha in subtree rooted at this node | |
Double_t | fNB |
sum of weights of background events from the pruning sample in this node | |
Float_t | fNBkgEvents |
sum of weights of backgr event in the node | |
Float_t | fNBkgEvents_unboosted |
sum of backgr event in the node | |
Float_t | fNBkgEvents_unweighted |
sum of backgr event in the node | |
Float_t | fNEvents |
number of events in that entered the node (during training) | |
Float_t | fNEvents_unboosted |
number of events in that entered the node (during training) | |
Float_t | fNEvents_unweighted |
number of events in that entered the node (during training) | |
Double_t | fNodeR |
node resubstitution estimate, R(t) | |
Double_t | fNS |
ditto for the signal events | |
Float_t | fNSigEvents |
sum of weights of signal event in the node | |
Float_t | fNSigEvents_unboosted |
sum of signal event in the node | |
Float_t | fNSigEvents_unweighted |
sum of signal event in the node | |
Int_t | fNTerminal |
number of terminal nodes in subtree rooted at this node | |
std::vector< Float_t > | fSampleMax |
the maxima for each ivar of the sample on the node during training | |
std::vector< Float_t > | fSampleMin |
the minima for each ivar of the sample on the node during training | |
Float_t | fSeparationGain |
measure of "purity", separation, or information gained BY this nodes selection | |
Float_t | fSeparationIndex |
measure of "purity" (separation between S and B) AT this node | |
Double_t | fSubTreeR |
R(T) = Sum(R(t) : t in ~T) | |
Float_t | fSumTarget |
sum of weight*target used for the calculation of the variance (regression) | |
Float_t | fSumTarget2 |
sum of weight*target^2 used for the calculation of the variance (regression) | |
#include <TMVA/DecisionTreeNode.h>
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inline |
Definition at line 54 of file DecisionTreeNode.h.
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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.