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ROOT
6.06/09
Reference Guide
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Public Member Functions | |
DataSet (const DataSetInfo &) | |
constructor More... | |
virtual | ~DataSet () |
destructor More... | |
void | AddEvent (Event *, Types::ETreeType) |
add event to event list after which the event is owned by the dataset More... | |
Long64_t | GetNEvents (Types::ETreeType type=Types::kMaxTreeType) const |
Long64_t | GetNTrainingEvents () const |
Long64_t | GetNTestEvents () const |
const Event * | GetEvent () const |
const Event * | GetEvent (Long64_t ievt) const |
const Event * | GetTrainingEvent (Long64_t ievt) const |
const Event * | GetTestEvent (Long64_t ievt) const |
const Event * | GetEvent (Long64_t ievt, Types::ETreeType type) const |
UInt_t | GetNVariables () const |
access the number of variables through the datasetinfo More... | |
UInt_t | GetNTargets () const |
access the number of targets through the datasetinfo More... | |
UInt_t | GetNSpectators () const |
access the number of targets through the datasetinfo More... | |
void | SetCurrentEvent (Long64_t ievt) const |
void | SetCurrentType (Types::ETreeType type) const |
Types::ETreeType | GetCurrentType () const |
void | SetEventCollection (std::vector< Event * > *, Types::ETreeType) |
Sets the event collection (by DataSetFactory) More... | |
const std::vector< Event * > & | GetEventCollection (Types::ETreeType type=Types::kMaxTreeType) const |
const TTree * | GetEventCollectionAsTree () |
Long64_t | GetNEvtSigTest () |
return number of signal test events in dataset More... | |
Long64_t | GetNEvtBkgdTest () |
return number of background test events in dataset More... | |
Long64_t | GetNEvtSigTrain () |
return number of signal training events in dataset More... | |
Long64_t | GetNEvtBkgdTrain () |
return number of background training events in dataset More... | |
Bool_t | HasNegativeEventWeights () const |
Results * | GetResults (const TString &, Types::ETreeType type, Types::EAnalysisType analysistype) |
TString info(resultsName+"/"); switch(type) { case Types::kTraining: info += "kTraining/"; break; case Types::kTesting: info += "kTesting/"; break; default: break; } switch(analysistype) { case Types::kClassification: info += "kClassification"; break; case Types::kRegression: info += "kRegression"; break; case Types::kNoAnalysisType: info += "kNoAnalysisType"; break; case Types::kMaxAnalysisType:info += "kMaxAnalysisType"; break; }. More... | |
void | DeleteResults (const TString &, Types::ETreeType type, Types::EAnalysisType analysistype) |
delete the results stored for this particulary Method instance (here appareantly called resultsName instead of MethodTitle Tree type (Training, testing etc..) Analysis Type (Classification, Multiclass, Regression etc..) More... | |
void | SetVerbose (Bool_t) |
void | DivideTrainingSet (UInt_t blockNum) |
divide training set More... | |
void | MoveTrainingBlock (Int_t blockInd, Types::ETreeType dest, Bool_t applyChanges=kTRUE) |
move training block More... | |
void | IncrementNClassEvents (Int_t type, UInt_t classNumber) |
Long64_t | GetNClassEvents (Int_t type, UInt_t classNumber) |
void | ClearNClassEvents (Int_t type) |
TTree * | GetTree (Types::ETreeType type) |
create the test/trainings tree with all the variables, the weights, the classes, the targets, the spectators, the MVA outputs More... | |
void | InitSampling (Float_t fraction, Float_t weight, UInt_t seed=0) |
initialize random or importance sampling More... | |
void | EventResult (Bool_t successful, Long64_t evtNumber=-1) |
increase the importance sampling weight of the event when not successful and decrease it when successful More... | |
void | CreateSampling () const |
create an event sampling (random or importance sampling) More... | |
UInt_t | TreeIndex (Types::ETreeType type) const |
Private Member Functions | |
DataSet () | |
void | DestroyCollection (Types::ETreeType type, Bool_t deleteEvents) |
destroys the event collection (events + vector) More... | |
MsgLogger & | Log () const |
void | ApplyTrainingBlockDivision () |
void | ApplyTrainingSetDivision () |
apply division of data set More... | |
Private Attributes | |
const DataSetInfo & | fdsi |
std::vector< Event * >::iterator | fEvtCollIt |
datasetinfo that created this dataset More... | |
std::vector< std::vector< Event * > * > | fEventCollection |
std::vector< std::map< TString, Results * > > | fResults |
list of events for training/testing/... More... | |
UInt_t | fCurrentTreeIdx |
[train/test/...][method-identifier] More... | |
Long64_t | fCurrentEventIdx |
std::vector< Char_t > | fSampling |
std::vector< Int_t > | fSamplingNEvents |
std::vector< Float_t > | fSamplingWeight |
std::vector< std::vector< std::pair< Float_t, Long64_t > * > > | fSamplingEventList |
std::vector< std::vector< std::pair< Float_t, Long64_t > * > > | fSamplingSelected |
TRandom3 * | fSamplingRandom |
std::vector< std::vector< Long64_t > > | fClassEvents |
Bool_t | fHasNegativeEventWeights |
number of events of class 0,1,2,... in training[0] More... | |
MsgLogger * | fLogger |
std::vector< Char_t > | fBlockBelongToTraining |
Long64_t | fTrainingBlockSize |
#include <TMVA/DataSet.h>
TMVA::DataSet::DataSet | ( | const DataSetInfo & | dsi | ) |
constructor
Definition at line 61 of file DataSet.cxx.
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destructor
Definition at line 94 of file DataSet.cxx.
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void TMVA::DataSet::AddEvent | ( | Event * | ev, |
Types::ETreeType | type | ||
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add event to event list after which the event is owned by the dataset
Definition at line 219 of file DataSet.cxx.
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apply division of data set
Definition at line 358 of file DataSet.cxx.
Definition at line 138 of file DataSet.cxx.
void TMVA::DataSet::CreateSampling | ( | ) | const |
create an event sampling (random or importance sampling)
Definition at line 472 of file DataSet.cxx.
void TMVA::DataSet::DeleteResults | ( | const TString & | resultsName, |
Types::ETreeType | type, | ||
Types::EAnalysisType | analysistype | ||
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delete the results stored for this particulary Method instance (here appareantly called resultsName instead of MethodTitle Tree type (Training, testing etc..) Analysis Type (Classification, Multiclass, Regression etc..)
Definition at line 308 of file DataSet.cxx.
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destroys the event collection (events + vector)
Definition at line 167 of file DataSet.cxx.
divide training set
Definition at line 334 of file DataSet.cxx.
increase the importance sampling weight of the event when not successful and decrease it when successful
Definition at line 536 of file DataSet.cxx.
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const TMVA::Event * TMVA::DataSet::GetEvent | ( | ) | const |
Definition at line 180 of file DataSet.cxx.
Referenced by TMVA::DataSetFactory::CalcCovarianceMatrix(), TMVA::DataSetFactory::CalcMinMax(), TMVA::ResultsMulticlass::CreateMulticlassHistos(), TMVA::ResultsRegression::DeviationAsAFunctionOf(), TMVA::ResultsMulticlass::EstimatorFunction(), TMVA::Factory::EvaluateAllMethods(), GetEvent(), TMVA::MethodPyAdaBoost::GetMvaValue(), TMVA::MethodPyRandomForest::GetMvaValue(), TMVA::MethodPyGTB::GetMvaValue(), GetTestEvent(), GetTrainingEvent(), TMVA::RMethodBase::LoadData(), TMVA::ResultsRegression::QuadraticDeviation(), and TMVA::CCTreeWrapper::TestTreeQuality().
Definition at line 95 of file DataSet.h.
Referenced by GetEvent().
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const TTree* TMVA::DataSet::GetEventCollectionAsTree | ( | ) |
Definition at line 146 of file DataSet.cxx.
Referenced by TMVA::DataSetFactory::BuildInitialDataSet().
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Definition at line 225 of file DataSet.h.
Referenced by TMVA::DataSetFactory::CalcCovarianceMatrix(), TMVA::DataSetFactory::CalcMinMax(), TMVA::DataSetFactory::CreateDataSet(), TMVA::ResultsMulticlass::CreateMulticlassHistos(), TMVA::ResultsRegression::DeviationAsAFunctionOf(), TMVA::ResultsMulticlass::EstimatorFunction(), TMVA::Factory::EvaluateAllMethods(), TMVA::MethodBase::GetNEvents(), GetNTestEvents(), GetNTrainingEvents(), TMVA::ResultsRegression::QuadraticDeviation(), and TMVA::CCTreeWrapper::TestTreeQuality().
Long64_t TMVA::DataSet::GetNEvtBkgdTest | ( | ) |
return number of background test events in dataset
Definition at line 398 of file DataSet.cxx.
Referenced by TMVA::Factory::EvaluateAllMethods().
Long64_t TMVA::DataSet::GetNEvtBkgdTrain | ( | ) |
return number of background training events in dataset
Definition at line 414 of file DataSet.cxx.
Referenced by TMVA::MethodRSVM::Train().
Long64_t TMVA::DataSet::GetNEvtSigTest | ( | ) |
return number of signal test events in dataset
Definition at line 390 of file DataSet.cxx.
Referenced by TMVA::Factory::EvaluateAllMethods().
Long64_t TMVA::DataSet::GetNEvtSigTrain | ( | ) |
return number of signal training events in dataset
Definition at line 406 of file DataSet.cxx.
Referenced by TMVA::MethodRSVM::Train().
UInt_t TMVA::DataSet::GetNSpectators | ( | ) | const |
access the number of targets through the datasetinfo
Definition at line 210 of file DataSet.cxx.
Referenced by TMVA::DataSetFactory::CalcMinMax().
UInt_t TMVA::DataSet::GetNTargets | ( | ) | const |
access the number of targets through the datasetinfo
Definition at line 202 of file DataSet.cxx.
Referenced by TMVA::DataSetFactory::CalcMinMax().
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Definition at line 91 of file DataSet.h.
Referenced by TMVA::RMethodBase::LoadData(), and TMVA::DataSetFactory::MixEvents().
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Definition at line 90 of file DataSet.h.
Referenced by TMVA::MethodBase::HasTrainingTree(), TMVA::MethodPyGTB::Init(), TMVA::MethodPyRandomForest::Init(), TMVA::MethodPyAdaBoost::Init(), TMVA::RMethodBase::LoadData(), TMVA::DataSetFactory::MixEvents(), TMVA::Factory::OptimizeAllMethods(), TMVA::MethodCategory::Train(), and TMVA::Factory::TrainAllMethods().
UInt_t TMVA::DataSet::GetNVariables | ( | ) | const |
access the number of variables through the datasetinfo
Definition at line 194 of file DataSet.cxx.
Referenced by TMVA::DataSetFactory::CalcCorrelationMatrix(), TMVA::DataSetFactory::CalcCovarianceMatrix(), TMVA::DataSetFactory::CalcMinMax(), TMVA::MethodPyGTB::Init(), TMVA::MethodPyRandomForest::Init(), and TMVA::MethodPyAdaBoost::Init().
TMVA::Results * TMVA::DataSet::GetResults | ( | const TString & | resultsName, |
Types::ETreeType | type, | ||
Types::EAnalysisType | analysistype | ||
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TString info(resultsName+"/"); switch(type) { case Types::kTraining: info += "kTraining/"; break; case Types::kTesting: info += "kTesting/"; break; default: break; } switch(analysistype) { case Types::kClassification: info += "kClassification"; break; case Types::kRegression: info += "kRegression"; break; case Types::kNoAnalysisType: info += "kNoAnalysisType"; break; case Types::kMaxAnalysisType:info += "kMaxAnalysisType"; break; }.
Definition at line 257 of file DataSet.cxx.
Referenced by TMVA::Factory::EvaluateAllMethods().
Definition at line 96 of file DataSet.h.
Referenced by TMVA::MethodPyAdaBoost::Init(), TMVA::MethodPyRandomForest::Init(), and TMVA::MethodPyGTB::Init().
TTree * TMVA::DataSet::GetTree | ( | Types::ETreeType | type | ) |
create the test/trainings tree with all the variables, the weights, the classes, the targets, the spectators, the MVA outputs
Definition at line 573 of file DataSet.cxx.
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Definition at line 129 of file DataSet.cxx.
initialize random or importance sampling
Definition at line 422 of file DataSet.cxx.
void TMVA::DataSet::MoveTrainingBlock | ( | Int_t | blockInd, |
Types::ETreeType | dest, | ||
Bool_t | applyChanges = kTRUE |
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move training block
Definition at line 378 of file DataSet.cxx.
Definition at line 110 of file DataSet.h.
Referenced by TMVA::DataSetFactory::BuildDynamicDataSet().
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Definition at line 111 of file DataSet.h.
Referenced by TMVA::DataSetFactory::BuildDynamicDataSet(), TMVA::ResultsMulticlass::CreateMulticlassHistos(), TMVA::ResultsRegression::DeviationAsAFunctionOf(), TMVA::ResultsMulticlass::EstimatorFunction(), TMVA::Factory::EvaluateAllMethods(), TMVA::ResultsRegression::QuadraticDeviation(), and TMVA::CCTreeWrapper::TestTreeQuality().
void TMVA::DataSet::SetEventCollection | ( | std::vector< Event * > * | events, |
Types::ETreeType | type | ||
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Sets the event collection (by DataSetFactory)
Definition at line 229 of file DataSet.cxx.
Referenced by TMVA::DataSetFactory::BuildDynamicDataSet(), and TMVA::DataSetFactory::MixEvents().
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Definition at line 200 of file DataSet.h.
Referenced by GetEvent(), and SetCurrentType().
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Definition at line 168 of file DataSet.h.
Referenced by GetEvent(), and SetCurrentEvent().
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[train/test/...][method-identifier]
Definition at line 167 of file DataSet.h.
Referenced by GetEvent(), SetCurrentType(), and TreeIndex().
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number of events of class 0,1,2,... in training[0]
Definition at line 183 of file DataSet.h.
Referenced by HasNegativeEventWeights().
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