12 #ifndef ROOT_TMVA_CROSS_EVALUATION 13 #define ROOT_TMVA_CROSS_EVALUATION 46 using EventCollection_t = std::vector<Event *>;
47 using EventTypes_t = std::vector<Bool_t>;
48 using EventOutputs_t = std::vector<Float_t>;
49 using EventOutputsMulticlass_t = std::vector<std::vector<Float_t>>;
80 std::map<UInt_t, Float_t>
fROCs;
100 Float_t GetROCStandardDeviation()
const;
130 void SetNumFolds(
UInt_t i);
131 void SetSplitExpr(
TString splitExpr);
138 const std::vector<CrossValidationResult> &GetResults()
const;
176 #endif // ROOT_TMVA_CROSS_EVALUATION
std::vector< Double_t > fSigs
CrossValidationFoldResult()
std::vector< Double_t > GetSepValues() const
TFile * fOutputFile
How to combine output of individual folds.
std::vector< Double_t > GetEffAreaValues() const
Bool_t fFoldStatus
If true: generate output file for each fold.
std::unique_ptr< CvSplitKFolds > fSplit
std::map< UInt_t, Float_t > fROCs
A ROOT file is a suite of consecutive data records (TKey instances) with a well defined format...
A TMultiGraph is a collection of TGraph (or derived) objects.
Class to save the results of cross validation, the metric for the classification ins ROC and you can ...
std::vector< Double_t > GetEff30Values() const
std::vector< Double_t > GetEff10Values() const
Types::EAnalysisType fAnalysisType
TString fOutputEnsembling
std::vector< Double_t > fEff10s
std::vector< Double_t > GetEff01Values() const
std::vector< Double_t > GetSigValues() const
#define ClassDef(name, id)
std::vector< CrossValidationResult > fResults
Abstract base class for all high level ml algorithms, you can book ml methods like BDT...
std::vector< Double_t > fTrainEff01s
UInt_t fNumWorkerProcs
Number of folds to prepare.
std::vector< Double_t > fTrainEff10s
TString fCvFactoryOptions
std::vector< Double_t > GetTrainEff10Values() const
CrossValidationFoldResult(UInt_t iFold)
std::vector< Double_t > fEff01s
This is the main MVA steering class.
std::vector< Double_t > fTrainEff30s
std::unique_ptr< Factory > fFoldFactory
void Print(std::ostream &os, const OptionType &opt)
Class to perform cross validation, splitting the dataloader into folds.
std::unique_ptr< Factory > fFactory
std::vector< Double_t > GetTrainEff01Values() const
std::vector< Double_t > fEffAreas
std::vector< Double_t > fSeps
Abstract ClassifierFactory template that handles arbitrary types.
std::vector< Double_t > GetTrainEff30Values() const
A Graph is a graphics object made of two arrays X and Y with npoints each.
std::vector< Double_t > fEff30s
std::shared_ptr< TMultiGraph > fROCCurves
TString fJobName
If true: dataset is prepared.
TString fOutputFactoryOptions
Number of processes to use for fold evaluation.
std::map< UInt_t, Float_t > GetROCValues() const