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TMVA::RegressionVariance Class Reference
TMVA

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.
 
virtual Double_t GetSeparationIndex (const Double_t n, const Double_t target, const Double_t target2)
 Separation Index: a simple Variance.
 
virtual TClass * IsA () const
 
virtual void Streamer (TBuffer &)
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 

Static Public Member Functions

static TClass * Class ()
 
static const char * Class_Name ()
 
static constexpr Version_t Class_Version ()
 
static const char * DeclFileName ()
 

Protected Attributes

TString fName
 name of the concrete Separation Index implementation
 

#include <TMVA/RegressionVariance.h>

Constructor & Destructor Documentation

◆ 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.

Member Function Documentation

◆ Class()

static TClass * TMVA::RegressionVariance::Class ( )
static
Returns
TClass describing this class

◆ Class_Name()

static const char * TMVA::RegressionVariance::Class_Name ( )
static
Returns
Name of this class

◆ Class_Version()

static constexpr Version_t TMVA::RegressionVariance::Class_Version ( )
inlinestaticconstexpr
Returns
Version of this class

Definition at line 94 of file RegressionVariance.h.

◆ DeclFileName()

static const char * TMVA::RegressionVariance::DeclFileName ( )
inlinestatic
Returns
Name of the file containing the class declaration

Definition at line 94 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 69 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 88 of file RegressionVariance.cxx.

◆ IsA()

virtual TClass * TMVA::RegressionVariance::IsA ( ) const
inlinevirtual
Returns
TClass describing current object

Definition at line 94 of file RegressionVariance.h.

◆ Streamer()

virtual void TMVA::RegressionVariance::Streamer ( TBuffer &  )
virtual

◆ StreamerNVirtual()

void TMVA::RegressionVariance::StreamerNVirtual ( TBuffer &  ClassDef_StreamerNVirtual_b)
inline

Definition at line 94 of file RegressionVariance.h.

Member Data Documentation

◆ fName

TString TMVA::RegressionVariance::fName
protected

name of the concrete Separation Index implementation

Definition at line 92 of file RegressionVariance.h.

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