26#ifndef ROOT_TMVA_MethodPyKeras
27#define ROOT_TMVA_MethodPyKeras
47 void Train()
override;
long long Long64_t
Portable signed long integer 8 bytes.
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char Pixmap_t Pixmap_t PictureAttributes_t attr const char char ret_data h unsigned char height h Atom_t Int_t ULong_t ULong_t unsigned char prop_list Atom_t Atom_t Atom_t Time_t type
A ROOT file is an on-disk file, usually with extension .root, that stores objects in a file-system-li...
Class that contains all the data information.
void GetHelpMessage() const override
void ProcessOptions() override
Function processing the options This is called only when creating the method before training not when...
std::vector< float > fOutput
std::vector< Float_t > & GetRegressionValues() override
const Ranking * CreateRanking() override
void AddWeightsXMLTo(void *) const override
Bool_t UseTFKeras() const
void ReadWeightsFromXML(void *) override
Int_t fTriesEarlyStopping
void ReadWeightsFromStream(TFile &) override
EBackendType
enumeration defining the used Keras backend
void SetupKerasModel(Bool_t loadTrainedModel)
Double_t GetMvaValue(Double_t *errLower, Double_t *errUpper) override
void DeclareOptions() override
UInt_t GetNumValidationSamples()
Validation of the ValidationSize option.
void TestClassification() override
initialization
void SetupKerasModelForEval()
Setting up model for evaluation Add here some needed optimizations like disabling eager execution.
ClassDefOverride(MethodPyKeras, 0)
bool fModelIsSetupForEval
TString fNumValidationString
std::vector< float > fVals
std::vector< Double_t > GetMvaValues(Long64_t firstEvt, Long64_t lastEvt, Bool_t logProgress) override
get all the MVA values for the events of the current Data type
TString GetKerasBackendName()
MethodPyKeras(const TString &jobName, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="")
TString fLearningRateSchedule
std::vector< Float_t > & GetMulticlassValues() override
void ReadWeightsFromStream(std::istream &) override
Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t) override
void Init() override
Initialization function called from MethodBase::SetupMethod() Note that option string are not yet fil...
void ReadModelFromFile() override
EBackendType GetKerasBackend()
Get the Keras backend (can be: TensorFlow, Theano or CNTK)
TString fFilenameTrainedModel
Virtual base class for all TMVA method based on Python.
Ranking for variables in method (implementation)
create variable transformations