TMVA::ROCCurve Class Reference

Definition at line 46 of file ROCCurve.h.

Public Member Functions
	ROCCurve (const std::vector< Float_t > &mvaSignal, const std::vector< Float_t > &mvaBackground)
	ROCCurve (const std::vector< Float_t > &mvaSignal, const std::vector< Float_t > &mvaBackground, const std::vector< Float_t > &mvaSignalWeights, const std::vector< Float_t > &mvaBackgroundWeights)
	ROCCurve (const std::vector< Float_t > &mvaValues, const std::vector< Bool_t > &mvaTargets)
	ROCCurve (const std::vector< Float_t > &mvaValues, const std::vector< Bool_t > &mvaTargets, const std::vector< Float_t > &mvaWeights)
	ROCCurve (const std::vector< std::tuple< Float_t, Float_t, Bool_t > > &mvas)
	~ROCCurve ()
	destructor
Double_t	GetEffSForEffB (Double_t effB, const UInt_t num_points=41)
	Calculate the signal efficiency (sensitivity) for a given background efficiency (sensitivity).
const std::vector< std::tuple< Float_t, Float_t, Bool_t > >	GetMvas () const
TGraph *	GetROCCurve (const UInt_t points=100)
	Returns a new TGraph containing the ROC curve.
Double_t	GetROCIntegral (const UInt_t points=41)
	Calculates the ROC integral (AUC)

Private Member Functions
std::vector< Double_t >	ComputeSensitivity (const UInt_t num_points)
std::vector< Double_t >	ComputeSpecificity (const UInt_t num_points)
MsgLogger &	Log () const

Private Attributes
TGraph *	fGraph
MsgLogger *	fLogger
	! message logger
std::vector< std::tuple< Float_t, Float_t, Bool_t > >	fMva

#include <TMVA/ROCCurve.h>

Constructor & Destructor Documentation

ROCCurve() [1/5]

TMVA::ROCCurve::ROCCurve

(

const std::vector< std::tuple< Float_t, Float_t, Bool_t > > &

mvas

)

Definition at line 45 of file ROCCurve.cxx.

ROCCurve() [2/5]

TMVA::ROCCurve::ROCCurve	(	const std::vector< Float_t > &	mvaValues,
		const std::vector< Bool_t > &	mvaTargets,
		const std::vector< Float_t > &	mvaWeights
	)

Definition at line 53 of file ROCCurve.cxx.

ROCCurve() [3/5]

TMVA::ROCCurve::ROCCurve	(	const std::vector< Float_t > &	mvaValues,
		const std::vector< Bool_t > &	mvaTargets
	)

Definition at line 70 of file ROCCurve.cxx.

ROCCurve() [4/5]

TMVA::ROCCurve::ROCCurve	(	const std::vector< Float_t > &	mvaSignal,
		const std::vector< Float_t > &	mvaBackground,
		const std::vector< Float_t > &	mvaSignalWeights,
		const std::vector< Float_t > &	mvaBackgroundWeights
	)

Definition at line 102 of file ROCCurve.cxx.

ROCCurve() [5/5]

TMVA::ROCCurve::ROCCurve	(	const std::vector< Float_t > &	mvaSignal,
		const std::vector< Float_t > &	mvaBackground
	)

Definition at line 85 of file ROCCurve.cxx.

~ROCCurve()

TMVA::ROCCurve::~ROCCurve

(

)

destructor

Definition at line 123 of file ROCCurve.cxx.

Member Function Documentation

ComputeSensitivity()

std::vector< Double_t > TMVA::ROCCurve::ComputeSensitivity ( const UInt_t  num_points )

private

Definition at line 174 of file ROCCurve.cxx.

ComputeSpecificity()

std::vector< Double_t > TMVA::ROCCurve::ComputeSpecificity ( const UInt_t  num_points )

private

Definition at line 138 of file ROCCurve.cxx.

GetEffSForEffB()

Double_t TMVA::ROCCurve::GetEffSForEffB	(	Double_t	effB,
		const UInt_t	num_points = 41
	)

Calculate the signal efficiency (sensitivity) for a given background efficiency (sensitivity).

Parameters

effB	Background efficiency for which to calculate signal efficiency.
num_points	Number of points used for the underlying histogram. The number of bins will be num_points - 1.

Definition at line 217 of file ROCCurve.cxx.

GetMvas()

const std::vector< std::tuple< Float_t, Float_t, Bool_t > > TMVA::ROCCurve::GetMvas ( ) const

inline

Definition at line 68 of file ROCCurve.h.

GetROCCurve()

TGraph * TMVA::ROCCurve::GetROCCurve

(

const UInt_t

num_points = 100

)

Returns a new TGraph containing the ROC curve.

Sensitivity is on the x-axis, specificity on the y-axis.

Parameters

num_points

Granularity of the resulting curve. The curve will be subdivided into num_points - 1 regions where the performance of the classifier is sampled. Larger number means more accurate, but more costly, evaluation.

Definition at line 274 of file ROCCurve.cxx.

GetROCIntegral()

Double_t TMVA::ROCCurve::GetROCIntegral

(

const UInt_t

num_points = 41

)

Calculates the ROC integral (AUC)

Parameters

num_points

Granularity of the resulting curve used for integration. The curve will be subdivided into num_points - 1 regions where the performance of the classifier is sampled. Larger number means more accurate, but more costly, evaluation.

Definition at line 248 of file ROCCurve.cxx.

Log()

TMVA::MsgLogger & TMVA::ROCCurve::Log ( ) const

private

Definition at line 128 of file ROCCurve.cxx.

Member Data Documentation

fGraph

TGraph* TMVA::ROCCurve::fGraph

private

Definition at line 73 of file ROCCurve.h.

fLogger

MsgLogger* TMVA::ROCCurve::fLogger

mutableprivate

! message logger

Definition at line 70 of file ROCCurve.h.

fMva

std::vector<std::tuple<Float_t, Float_t, Bool_t> > TMVA::ROCCurve::fMva

private

Definition at line 75 of file ROCCurve.h.

Libraries for TMVA::ROCCurve:

---

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

• tmva/tmva/inc/TMVA/ROCCurve.h
• tmva/tmva/src/ROCCurve.cxx