ROOT   Reference Guide
TMVA::DTNodeTrainingInfo Class Reference

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_tfSampleMax
the maxima for each ivar of the sample on the node during training More...

std::vector< Float_tfSampleMin
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>

## ◆ DTNodeTrainingInfo() [1/2]

 TMVA::DTNodeTrainingInfo::DTNodeTrainingInfo ( )
inline

Definition at line 54 of file DecisionTreeNode.h.

## ◆ DTNodeTrainingInfo() [2/2]

 TMVA::DTNodeTrainingInfo::DTNodeTrainingInfo ( const DTNodeTrainingInfo & n )
inline

Definition at line 96 of file DecisionTreeNode.h.

## ◆ fAlpha

 Double_t TMVA::DTNodeTrainingInfo::fAlpha

critical alpha for this node

Definition at line 74 of file DecisionTreeNode.h.

## ◆ fCC

 Double_t TMVA::DTNodeTrainingInfo::fCC

debug variable for cost complexity pruning ..

Definition at line 81 of file DecisionTreeNode.h.

## ◆ fG

 Double_t TMVA::DTNodeTrainingInfo::fG

minimum alpha in subtree rooted at this node

Definition at line 75 of file DecisionTreeNode.h.

## ◆ fNB

 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.

## ◆ fNBkgEvents

 Float_t TMVA::DTNodeTrainingInfo::fNBkgEvents

sum of weights of backgr event in the node

Definition at line 84 of file DecisionTreeNode.h.

## ◆ fNBkgEvents_unboosted

 Float_t TMVA::DTNodeTrainingInfo::fNBkgEvents_unboosted

sum of backgr event in the node

Definition at line 90 of file DecisionTreeNode.h.

## ◆ fNBkgEvents_unweighted

 Float_t TMVA::DTNodeTrainingInfo::fNBkgEvents_unweighted

sum of backgr event in the node

Definition at line 87 of file DecisionTreeNode.h.

## ◆ fNEvents

 Float_t TMVA::DTNodeTrainingInfo::fNEvents

number of events in that entered the node (during training)

Definition at line 85 of file DecisionTreeNode.h.

## ◆ fNEvents_unboosted

 Float_t TMVA::DTNodeTrainingInfo::fNEvents_unboosted

number of events in that entered the node (during training)

Definition at line 91 of file DecisionTreeNode.h.

## ◆ fNEvents_unweighted

 Float_t TMVA::DTNodeTrainingInfo::fNEvents_unweighted

number of events in that entered the node (during training)

Definition at line 88 of file DecisionTreeNode.h.

## ◆ fNodeR

 Double_t TMVA::DTNodeTrainingInfo::fNodeR

node resubstitution estimate, R(t)

Definition at line 72 of file DecisionTreeNode.h.

## ◆ fNS

 Double_t TMVA::DTNodeTrainingInfo::fNS

ditto for the signal events

Definition at line 78 of file DecisionTreeNode.h.

## ◆ fNSigEvents

 Float_t TMVA::DTNodeTrainingInfo::fNSigEvents

sum of weights of signal event in the node

Definition at line 83 of file DecisionTreeNode.h.

## ◆ fNSigEvents_unboosted

 Float_t TMVA::DTNodeTrainingInfo::fNSigEvents_unboosted

sum of signal event in the node

Definition at line 89 of file DecisionTreeNode.h.

## ◆ fNSigEvents_unweighted

 Float_t TMVA::DTNodeTrainingInfo::fNSigEvents_unweighted

sum of signal event in the node

Definition at line 86 of file DecisionTreeNode.h.

## ◆ fNTerminal

 Int_t TMVA::DTNodeTrainingInfo::fNTerminal

number of terminal nodes in subtree rooted at this node

Definition at line 76 of file DecisionTreeNode.h.

## ◆ fSampleMax

 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.

## ◆ fSampleMin

 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.

## ◆ fSeparationGain

 Float_t TMVA::DTNodeTrainingInfo::fSeparationGain

measure of "purity", separation, or information gained BY this nodes selection

Definition at line 93 of file DecisionTreeNode.h.

## ◆ fSeparationIndex

 Float_t TMVA::DTNodeTrainingInfo::fSeparationIndex

measure of "purity" (separation between S and B) AT this node

Definition at line 92 of file DecisionTreeNode.h.

## ◆ fSubTreeR

 Double_t TMVA::DTNodeTrainingInfo::fSubTreeR

R(T) = Sum(R(t) : t in ~T)

Definition at line 73 of file DecisionTreeNode.h.

## ◆ fSumTarget

 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.

## ◆ fSumTarget2

 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.

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