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class TMVA::RegressionVariance

Function Members (Methods)

public:
virtual~RegressionVariance()
static TClass*Class()
TStringGetName()
Double_tGetSeparationGain(const Double_t& nLeft, const Double_t& targetLeft, const Double_t& target2Left, const Double_t& nTot, const Double_t& targetTot, const Double_t& target2Tot)
virtual Double_tGetSeparationIndex(const Double_t& n, const Double_t& target, const Double_t& target2)
virtual TClass*IsA() const
TMVA::RegressionVariance&operator=(const TMVA::RegressionVariance&)
TMVA::RegressionVarianceRegressionVariance()
TMVA::RegressionVarianceRegressionVariance(const TMVA::RegressionVariance& s)
virtual voidShowMembers(TMemberInspector& insp, char* parent)
virtual voidStreamer(TBuffer& b)
voidStreamerNVirtual(TBuffer& b)

Data Members

protected:
TStringfNamename of the concrete Separation Index impementation

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

Function documentation

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. into a "left-node" and a "right-node"
 (N * Index_parent) - (N_left * Index_left) - (N_right * Index_right)
 this is then the quality crition which is optimized for when trying
 to increase the information in the system (making the best selection
Double_t GetSeparationIndex(const Double_t& n, const Double_t& target, const Double_t& target2)
 Separation Index:  a simple Variance
RegressionVariance()
default constructor
{fName = "Variance for Regression";}
RegressionVariance(const TMVA::RegressionVariance& s)
copy constructor
{}
virtual ~RegressionVariance()
 destructor
{}
TString GetName()
 Return the name of the concrete Index implementation
{ return fName; }