ROOT 6.10/09 Reference Guide |
Implementation of the GiniIndex as separation criterion.
Large Gini Indices (maximum 0.5) mean , that the sample is well mixed (same amount of signal and bkg) bkg.
Small Indices mean, well separated.
\[ Gini(Sample M) = 1 - (\frac{c(1)}{N})^2 - (\frac{c(2)}{N})^2 .... - (\frac{c(k)}{N})^2 \]
Where:
\( M \) is a sample of whatever \( N \) elements (events) that belong to \( K \) different classes.
\( c(k) \) is the number of elements that belong to class \( k \) for just Signal and Background classes this boils down to:
\[ Gini(Sample) = \frac{2sb}{(s+b)^2} \]
Definition at line 63 of file GiniIndex.h.
Public Member Functions | |
GiniIndex () | |
GiniIndex (const GiniIndex &g) | |
virtual | ~GiniIndex () |
virtual Double_t | GetSeparationIndex (const Double_t s, const Double_t b) |
what we use here is 2*Gini. More... | |
Public Member Functions inherited from TMVA::SeparationBase | |
SeparationBase () | |
Constructor. More... | |
SeparationBase (const SeparationBase &s) | |
Copy constructor. More... | |
virtual | ~SeparationBase () |
const TString & | GetName () |
virtual Double_t | GetSeparationGain (const Double_t nSelS, const Double_t nSelB, const Double_t nTotS, const Double_t nTotB) |
Separation Gain: the measure of how the quality of separation of the sample increases by splitting the sample e.g. More... | |
Additional Inherited Members | |
Protected Attributes inherited from TMVA::SeparationBase | |
TString | fName |
Double_t | fPrecisionCut |
#include <TMVA/GiniIndex.h>
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inline |
Definition at line 68 of file GiniIndex.h.
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inline |
Definition at line 71 of file GiniIndex.h.
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inlinevirtual |
Definition at line 74 of file GiniIndex.h.
what we use here is 2*Gini.
. as for the later use the factor 2 is irrelevant and hence I'd like to save this calculation
Implements TMVA::SeparationBase.
Definition at line 76 of file GiniIndex.cxx.