 ROOT   6.14/05 Reference Guide
TMVA::RegressionVariance Class Reference

Calculate the "SeparationGain" for Regression analysis separation criteria used in various training algorithms.

There are two things: the Separation Index, and the Separation Gain Separation Index: Measure of the "Variance" of a sample.

Separation Gain: the measure of how the quality of separation of the sample increases by splitting the sample e.g. into a "left-node" and a "right-node" (N * Index_parent) - (N_left * Index_left) - (N_right * Index_right) this is then the quality criteria which is optimized for when trying to increase the information in the system (making the best selection

Definition at line 66 of file RegressionVariance.h.

## Public Member Functions

RegressionVariance ()

RegressionVariance (const RegressionVariance &s)

virtual ~RegressionVariance ()

TString GetName ()

Double_t GetSeparationGain (const Double_t nLeft, const Double_t targetLeft, const Double_t target2Left, const Double_t nTot, const Double_t targetTot, const Double_t target2Tot)
Separation Gain: the measure of how the quality of separation of the sample increases by splitting the sample e.g. More...

virtual Double_t GetSeparationIndex (const Double_t n, const Double_t target, const Double_t target2)
Separation Index: a simple Variance. More...

## Protected Attributes

TString fName

#include <TMVA/RegressionVariance.h>

## ◆ RegressionVariance() [1/2]

 TMVA::RegressionVariance::RegressionVariance ( )
inline

Definition at line 71 of file RegressionVariance.h.

## ◆ RegressionVariance() [2/2]

 TMVA::RegressionVariance::RegressionVariance ( const RegressionVariance & s )
inline

Definition at line 74 of file RegressionVariance.h.

## ◆ ~RegressionVariance()

 virtual TMVA::RegressionVariance::~RegressionVariance ( )
inlinevirtual

Definition at line 77 of file RegressionVariance.h.

## ◆ GetName()

 TString TMVA::RegressionVariance::GetName ( )
inline

Definition at line 88 of file RegressionVariance.h.

## ◆ GetSeparationGain()

 Double_t TMVA::RegressionVariance::GetSeparationGain ( const Double_t nLeft, const Double_t targetLeft, const Double_t target2Left, const Double_t nTot, const Double_t targetTot, const Double_t target2Tot )

Separation Gain: the measure of how the quality of separation of the sample increases by splitting the sample e.g.

into a "left-node" and a "right-node" (N * Index_parent) - (N_left * Index_left) - (N_right * Index_right) this is then the quality criteria which is optimized for when trying to increase the information in the system for the Regression: as the "Gain is maximised", the RMS (sqrt(variance)) which is used as a "separation" index should be as small as possible. the "figure of merit" here has to be -(rms left+rms-right) or 1/rms...

Definition at line 70 of file RegressionVariance.cxx.

## ◆ GetSeparationIndex()

 Double_t TMVA::RegressionVariance::GetSeparationIndex ( const Double_t n, const Double_t target, const Double_t target2 )
virtual

Separation Index: a simple Variance.

Definition at line 89 of file RegressionVariance.cxx.

## ◆ fName

 TString TMVA::RegressionVariance::fName
protected

Definition at line 92 of file RegressionVariance.h.

Libraries for TMVA::RegressionVariance: [legend]

The documentation for this class was generated from the following files: