Logo ROOT  

Reference Guide
 
Loading...
Searching...
No Matches
List of all members | Public Member Functions | Static Public Member Functions | Private Member Functions | Private Attributes | Static Private Attributes | List of all members
TMVA::RuleFit Class Reference
TMVA

A class implementing various fits of rule ensembles.

Definition at line 46 of file RuleFit.h.

Public Member Functions

 RuleFit (const TMVA::MethodBase *rfbase)
 constructor
 
 RuleFit (void)
 default constructor
 
virtual ~RuleFit (void)
 destructor
 
void Boost (TMVA::DecisionTree *dt)
 Boost the events.
 
void BuildTree (TMVA::DecisionTree *dt)
 build the decision tree using fNTreeSample events from fTrainingEventsRndm
 
void CalcImportance ()
 calculates the importance of each rule
 
Double_t CalcWeightSum (const std::vector< const TMVA::Event * > *events, UInt_t neve=0)
 calculate the sum of weights
 
Double_t EvalEvent (const Event &e)
 evaluate single event
 
void FillCorr (TH2F *h2, const TMVA::Rule *rule, Int_t v1, Int_t v2)
 fill rule correlation between vx and vy, weighted with either the importance or the coefficient
 
void FillCut (TH2F *h2, const TMVA::Rule *rule, Int_t vind)
 Fill cut.
 
void FillLin (TH2F *h2, Int_t vind)
 fill lin
 
void FillVisHistCorr (const Rule *rule, std::vector< TH2F * > &hlist)
 help routine to MakeVisHists() - fills for all correlation plots
 
void FillVisHistCut (const Rule *rule, std::vector< TH2F * > &hlist)
 help routine to MakeVisHists() - fills for all variables
 
void FitCoefficients ()
 Fit the coefficients for the rule ensemble.
 
void ForestStatistics ()
 summary of statistics of all trees
 
Bool_t GetCorrVars (TString &title, TString &var1, TString &var2)
 get first and second variables from title
 
const std::vector< const TMVA::DecisionTree * > & GetForest () const
 
const MethodBase * GetMethodBase () const
 
const MethodRuleFit * GetMethodRuleFit () const
 
Double_t GetNEveEff () const
 
UInt_t GetNTreeSample () const
 
void GetRndmSampleEvents (std::vector< const TMVA::Event * > &evevec, UInt_t nevents)
 draw a random subsample of the training events without replacement
 
const RuleEnsemble & GetRuleEnsemble () const
 
RuleEnsemble * GetRuleEnsemblePtr ()
 
const RuleFitParams & GetRuleFitParams () const
 
RuleFitParams * GetRuleFitParamsPtr ()
 
const Event * GetTrainingEvent (UInt_t i) const
 
const std::vector< const TMVA::Event * > & GetTrainingEvents () const
 
Double_t GetTrainingEventWeight (UInt_t i) const
 
void Initialize (const TMVA::MethodBase *rfbase)
 initialize the parameters of the RuleFit method and make rules
 
void InitNEveEff ()
 init effective number of events (using event weights)
 
void InitPtrs (const TMVA::MethodBase *rfbase)
 initialize pointers
 
virtual TClass * IsA () const
 
void MakeDebugHists ()
 this will create a histograms intended rather for debugging or for the curious user
 
void MakeForest ()
 make a forest of decisiontrees
 
void MakeVisHists ()
 this will create histograms visualizing the rule ensemble
 
void NormVisHists (std::vector< TH2F * > &hlist)
 normalize rule importance hists
 
void ReshuffleEvents ()
 
void RestoreEventWeights ()
 save event weights - must be done before making the forest
 
void SaveEventWeights ()
 save event weights - must be done before making the forest
 
void SetGDNPathSteps (Int_t n=100)
 
void SetGDPathStep (Double_t s=0.01)
 
void SetGDTau (Double_t t=0.0)
 
void SetImportanceCut (Double_t minimp=0)
 
void SetMethodBase (const MethodBase *rfbase)
 set MethodBase
 
void SetModelFull ()
 
void SetModelLinear ()
 
void SetModelRules ()
 
void SetMsgType (EMsgType t)
 set the current message type to that of mlog for this class and all other subtools
 
void SetRuleMinDist (Double_t d)
 
void SetTrainingEvents (const std::vector< const TMVA::Event * > &el)
 set the training events randomly
 
void SetVisHistsUseImp (Bool_t f)
 
virtual void Streamer (TBuffer &)
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
void UseCoefficientsVisHists ()
 
void UseImportanceVisHists ()
 

Static Public Member Functions

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

Private Member Functions

 RuleFit (const RuleFit &other)
 
void Copy (const RuleFit &other)
 copy method
 
MsgLogger & Log () const
 

Private Attributes

std::vector< Double_t > fEventWeights
 original weights of the events - follows fTrainingEvents
 
std::vector< const TMVA::DecisionTree * > fForest
 the input forest of decision trees
 
MsgLogger * fLogger
 ! message logger
 
const MethodBase * fMethodBase
 pointer the method base which initialized this RuleFit instance
 
const MethodRuleFit * fMethodRuleFit
 pointer the method which initialized this RuleFit instance
 
Double_t fNEveEffTrain
 reweighted number of events = sum(wi)
 
UInt_t fNTreeSample
 number of events in sub sample = frac*neve
 
std::default_random_engine fRNGEngine
 
RuleEnsemble fRuleEnsemble
 the ensemble of rules
 
RuleFitParams fRuleFitParams
 fit rule parameters
 
std::vector< const TMVA::Event * > fTrainingEvents
 all training events
 
std::vector< const TMVA::Event * > fTrainingEventsRndm
 idem, but randomly shuffled
 
Bool_t fVisHistsUseImp
 if true, use importance as weight; else coef in vis hists
 

Static Private Attributes

static const Int_t randSEED = 0
 

#include <TMVA/RuleFit.h>

Constructor & Destructor Documentation

◆ RuleFit() [1/3]

TMVA::RuleFit::RuleFit ( const TMVA::MethodBase * rfbase)

constructor

Definition at line 64 of file RuleFit.cxx.

◆ RuleFit() [2/3]

TMVA::RuleFit::RuleFit ( void )

default constructor

Definition at line 75 of file RuleFit.cxx.

◆ ~RuleFit()

TMVA::RuleFit::~RuleFit ( void )
virtual

destructor

Definition at line 89 of file RuleFit.cxx.

◆ RuleFit() [3/3]

TMVA::RuleFit::RuleFit ( const RuleFit & other)
private

Member Function Documentation

◆ Boost()

void TMVA::RuleFit::Boost ( TMVA::DecisionTree * dt)

Boost the events.

The algorithm below is the called AdaBoost. See MethodBDT for details. Actually, this is a more or less copy of MethodBDT::AdaBoost().

Definition at line 328 of file RuleFit.cxx.

◆ BuildTree()

void TMVA::RuleFit::BuildTree ( TMVA::DecisionTree * dt)

build the decision tree using fNTreeSample events from fTrainingEventsRndm

Definition at line 200 of file RuleFit.cxx.

◆ CalcImportance()

void TMVA::RuleFit::CalcImportance ( )

calculates the importance of each rule

Definition at line 407 of file RuleFit.cxx.

◆ CalcWeightSum()

Double_t TMVA::RuleFit::CalcWeightSum ( const std::vector< const TMVA::Event * > * events,
UInt_t neve = 0 )

calculate the sum of weights

Definition at line 175 of file RuleFit.cxx.

◆ Class()

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

◆ Class_Name()

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

◆ Class_Version()

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

Definition at line 179 of file RuleFit.h.

◆ Copy()

void TMVA::RuleFit::Copy ( const RuleFit & other)
private

copy method

Definition at line 159 of file RuleFit.cxx.

◆ DeclFileName()

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

Definition at line 179 of file RuleFit.h.

◆ EvalEvent()

Double_t TMVA::RuleFit::EvalEvent ( const Event & e)

evaluate single event

Definition at line 421 of file RuleFit.cxx.

◆ FillCorr()

void TMVA::RuleFit::FillCorr ( TH2F * h2,
const TMVA::Rule * rule,
Int_t v1,
Int_t v2 )

fill rule correlation between vx and vy, weighted with either the importance or the coefficient

Definition at line 597 of file RuleFit.cxx.

◆ FillCut()

void TMVA::RuleFit::FillCut ( TH2F * h2,
const TMVA::Rule * rule,
Int_t vind )

Fill cut.

Definition at line 522 of file RuleFit.cxx.

◆ FillLin()

void TMVA::RuleFit::FillLin ( TH2F * h2,
Int_t vind )

fill lin

Definition at line 573 of file RuleFit.cxx.

◆ FillVisHistCorr()

void TMVA::RuleFit::FillVisHistCorr ( const Rule * rule,
std::vector< TH2F * > & hlist )

help routine to MakeVisHists() - fills for all correlation plots

Definition at line 704 of file RuleFit.cxx.

◆ FillVisHistCut()

void TMVA::RuleFit::FillVisHistCut ( const Rule * rule,
std::vector< TH2F * > & hlist )

help routine to MakeVisHists() - fills for all variables

Definition at line 673 of file RuleFit.cxx.

◆ FitCoefficients()

void TMVA::RuleFit::FitCoefficients ( )

Fit the coefficients for the rule ensemble.

Definition at line 398 of file RuleFit.cxx.

◆ ForestStatistics()

void TMVA::RuleFit::ForestStatistics ( )

summary of statistics of all trees

  • end-nodes: average and spread

Definition at line 375 of file RuleFit.cxx.

◆ GetCorrVars()

Bool_t TMVA::RuleFit::GetCorrVars ( TString & title,
TString & var1,
TString & var2 )

get first and second variables from title

Definition at line 743 of file RuleFit.cxx.

◆ GetForest()

const std::vector< const TMVA::DecisionTree * > & TMVA::RuleFit::GetForest ( ) const
inline

Definition at line 144 of file RuleFit.h.

◆ GetMethodBase()

const MethodBase * TMVA::RuleFit::GetMethodBase ( ) const
inline

Definition at line 150 of file RuleFit.h.

◆ GetMethodRuleFit()

const MethodRuleFit * TMVA::RuleFit::GetMethodRuleFit ( ) const
inline

Definition at line 149 of file RuleFit.h.

◆ GetNEveEff()

Double_t TMVA::RuleFit::GetNEveEff ( ) const
inline

Definition at line 132 of file RuleFit.h.

◆ GetNTreeSample()

UInt_t TMVA::RuleFit::GetNTreeSample ( ) const
inline

Definition at line 131 of file RuleFit.h.

◆ GetRndmSampleEvents()

void TMVA::RuleFit::GetRndmSampleEvents ( std::vector< const TMVA::Event * > & evevec,
UInt_t nevents )

draw a random subsample of the training events without replacement

Definition at line 456 of file RuleFit.cxx.

◆ GetRuleEnsemble()

const RuleEnsemble & TMVA::RuleFit::GetRuleEnsemble ( ) const
inline

Definition at line 145 of file RuleFit.h.

◆ GetRuleEnsemblePtr()

RuleEnsemble * TMVA::RuleFit::GetRuleEnsemblePtr ( )
inline

Definition at line 146 of file RuleFit.h.

◆ GetRuleFitParams()

const RuleFitParams & TMVA::RuleFit::GetRuleFitParams ( ) const
inline

Definition at line 147 of file RuleFit.h.

◆ GetRuleFitParamsPtr()

RuleFitParams * TMVA::RuleFit::GetRuleFitParamsPtr ( )
inline

Definition at line 148 of file RuleFit.h.

◆ GetTrainingEvent()

const Event * TMVA::RuleFit::GetTrainingEvent ( UInt_t i) const
inline

Definition at line 133 of file RuleFit.h.

◆ GetTrainingEvents()

const std::vector< const TMVA::Event * > & TMVA::RuleFit::GetTrainingEvents ( ) const
inline

Definition at line 138 of file RuleFit.h.

◆ GetTrainingEventWeight()

Double_t TMVA::RuleFit::GetTrainingEventWeight ( UInt_t i) const
inline

Definition at line 134 of file RuleFit.h.

◆ Initialize()

void TMVA::RuleFit::Initialize ( const TMVA::MethodBase * rfbase)

initialize the parameters of the RuleFit method and make rules

Definition at line 119 of file RuleFit.cxx.

◆ InitNEveEff()

void TMVA::RuleFit::InitNEveEff ( )

init effective number of events (using event weights)

Definition at line 97 of file RuleFit.cxx.

◆ InitPtrs()

void TMVA::RuleFit::InitPtrs ( const TMVA::MethodBase * rfbase)

initialize pointers

Definition at line 109 of file RuleFit.cxx.

◆ IsA()

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

Definition at line 179 of file RuleFit.h.

◆ Log()

MsgLogger & TMVA::RuleFit::Log ( ) const
inlineprivate

Definition at line 174 of file RuleFit.h.

◆ MakeDebugHists()

void TMVA::RuleFit::MakeDebugHists ( )

this will create a histograms intended rather for debugging or for the curious user

Definition at line 926 of file RuleFit.cxx.

◆ MakeForest()

void TMVA::RuleFit::MakeForest ( )

make a forest of decisiontrees

Definition at line 221 of file RuleFit.cxx.

◆ MakeVisHists()

void TMVA::RuleFit::MakeVisHists ( )

this will create histograms visualizing the rule ensemble

Definition at line 766 of file RuleFit.cxx.

◆ NormVisHists()

void TMVA::RuleFit::NormVisHists ( std::vector< TH2F * > & hlist)

normalize rule importance hists

if all weights are positive, the scale will be 1/maxweight if minimum weight < 0, then the scale will be 1/max(maxweight,abs(minweight))

Definition at line 475 of file RuleFit.cxx.

◆ ReshuffleEvents()

void TMVA::RuleFit::ReshuffleEvents ( )
inline

Definition at line 66 of file RuleFit.h.

◆ RestoreEventWeights()

void TMVA::RuleFit::RestoreEventWeights ( )

save event weights - must be done before making the forest

Definition at line 310 of file RuleFit.cxx.

◆ SaveEventWeights()

void TMVA::RuleFit::SaveEventWeights ( )

save event weights - must be done before making the forest

Definition at line 298 of file RuleFit.cxx.

◆ SetGDNPathSteps()

void TMVA::RuleFit::SetGDNPathSteps ( Int_t n = 100)
inline

Definition at line 116 of file RuleFit.h.

◆ SetGDPathStep()

void TMVA::RuleFit::SetGDPathStep ( Double_t s = 0.01)
inline

Definition at line 115 of file RuleFit.h.

◆ SetGDTau()

void TMVA::RuleFit::SetGDTau ( Double_t t = 0.0)
inline

Definition at line 114 of file RuleFit.h.

◆ SetImportanceCut()

void TMVA::RuleFit::SetImportanceCut ( Double_t minimp = 0)
inline

Definition at line 110 of file RuleFit.h.

◆ SetMethodBase()

void TMVA::RuleFit::SetMethodBase ( const MethodBase * rfbase)

set MethodBase

Definition at line 150 of file RuleFit.cxx.

◆ SetModelFull()

void TMVA::RuleFit::SetModelFull ( )
inline

Definition at line 108 of file RuleFit.h.

◆ SetModelLinear()

void TMVA::RuleFit::SetModelLinear ( )
inline

Definition at line 104 of file RuleFit.h.

◆ SetModelRules()

void TMVA::RuleFit::SetModelRules ( )
inline

Definition at line 106 of file RuleFit.h.

◆ SetMsgType()

void TMVA::RuleFit::SetMsgType ( EMsgType t)

set the current message type to that of mlog for this class and all other subtools

Definition at line 190 of file RuleFit.cxx.

◆ SetRuleMinDist()

void TMVA::RuleFit::SetRuleMinDist ( Double_t d)
inline

Definition at line 112 of file RuleFit.h.

◆ SetTrainingEvents()

void TMVA::RuleFit::SetTrainingEvents ( const std::vector< const TMVA::Event * > & el)

set the training events randomly

Definition at line 429 of file RuleFit.cxx.

◆ SetVisHistsUseImp()

void TMVA::RuleFit::SetVisHistsUseImp ( Bool_t f)
inline

Definition at line 118 of file RuleFit.h.

◆ Streamer()

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

◆ StreamerNVirtual()

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

Definition at line 179 of file RuleFit.h.

◆ UseCoefficientsVisHists()

void TMVA::RuleFit::UseCoefficientsVisHists ( )
inline

Definition at line 120 of file RuleFit.h.

◆ UseImportanceVisHists()

void TMVA::RuleFit::UseImportanceVisHists ( )
inline

Definition at line 119 of file RuleFit.h.

Member Data Documentation

◆ fEventWeights

std::vector<Double_t> TMVA::RuleFit::fEventWeights
private

original weights of the events - follows fTrainingEvents

Definition at line 162 of file RuleFit.h.

◆ fForest

std::vector< const TMVA::DecisionTree *> TMVA::RuleFit::fForest
private

the input forest of decision trees

Definition at line 166 of file RuleFit.h.

◆ fLogger

MsgLogger* TMVA::RuleFit::fLogger
mutableprivate

! message logger

Definition at line 173 of file RuleFit.h.

◆ fMethodBase

const MethodBase* TMVA::RuleFit::fMethodBase
private

pointer the method base which initialized this RuleFit instance

Definition at line 170 of file RuleFit.h.

◆ fMethodRuleFit

const MethodRuleFit* TMVA::RuleFit::fMethodRuleFit
private

pointer the method which initialized this RuleFit instance

Definition at line 169 of file RuleFit.h.

◆ fNEveEffTrain

Double_t TMVA::RuleFit::fNEveEffTrain
private

reweighted number of events = sum(wi)

Definition at line 165 of file RuleFit.h.

◆ fNTreeSample

UInt_t TMVA::RuleFit::fNTreeSample
private

number of events in sub sample = frac*neve

Definition at line 163 of file RuleFit.h.

◆ fRNGEngine

std::default_random_engine TMVA::RuleFit::fRNGEngine
private

Definition at line 177 of file RuleFit.h.

◆ fRuleEnsemble

RuleEnsemble TMVA::RuleFit::fRuleEnsemble
private

the ensemble of rules

Definition at line 167 of file RuleFit.h.

◆ fRuleFitParams

RuleFitParams TMVA::RuleFit::fRuleFitParams
private

fit rule parameters

Definition at line 168 of file RuleFit.h.

◆ fTrainingEvents

std::vector<const TMVA::Event *> TMVA::RuleFit::fTrainingEvents
private

all training events

Definition at line 160 of file RuleFit.h.

◆ fTrainingEventsRndm

std::vector<const TMVA::Event *> TMVA::RuleFit::fTrainingEventsRndm
private

idem, but randomly shuffled

Definition at line 161 of file RuleFit.h.

◆ fVisHistsUseImp

Bool_t TMVA::RuleFit::fVisHistsUseImp
private

if true, use importance as weight; else coef in vis hists

Definition at line 171 of file RuleFit.h.

◆ randSEED

const Int_t TMVA::RuleFit::randSEED = 0
staticprivate

Definition at line 176 of file RuleFit.h.

Libraries for TMVA::RuleFit:
[legend]
The documentation for this class was generated from the following files: