Belle II Software  release-08-01-10
Public Member Functions | Protected Attributes | List of all members
TMVAExpert Class Referenceabstract

Expert for the TMVA MVA method. More...

#include <TMVA.h>

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Public Member Functions

virtual void load (Weightfile &weightfile) override
 Load the expert from a Weightfile. More...
 
virtual std::vector< float > apply (Dataset &test_data) const =0
 Apply this expert onto a dataset. More...
 
virtual std::vector< std::vector< float > > applyMulticlass (Dataset &test_data) const
 Apply this m_expert onto a dataset. More...
 

Protected Attributes

std::unique_ptr< TMVA::Reader > m_expert
 TMVA::Reader pointer.
 
std::vector< float > m_input_cache
 Input Cache for TMVA::Reader: Otherwise we would have to set the branch addresses in each apply call.
 
std::vector< float > m_spectators_cache
 Spectators Cache for TMVA::Reader: Otherwise we would have to set the branch addresses in each apply call.
 
GeneralOptions m_general_options
 General options loaded from the weightfile.
 

Detailed Description

Expert for the TMVA MVA method.

Definition at line 284 of file TMVA.h.

Member Function Documentation

◆ apply()

virtual std::vector<float> apply ( Dataset &  test_data) const
pure virtualinherited

Apply this expert onto a dataset.

Parameters
test_datadataset

Implemented in TrivialExpert, TMVAExpertRegression, TMVAExpertMulticlass, TMVAExpertClassification, ReweighterExpert, RegressionExpert< BaseClassifierExpert, RegressionClassifierOptions >, PythonExpert, PDFExpert, FastBDTExpert, FANNExpert, and CombinationExpert.

◆ applyMulticlass()

virtual std::vector<std::vector<float> > applyMulticlass ( Dataset &  test_data) const
inlinevirtualinherited

Apply this m_expert onto a dataset.

Multiclass mode. Not pure virtual, since not all derived classes to re-implement this.

Parameters
test_datadataset.
Returns
vector of size N=test_data.getNumberOfEvents() with N=m_classes.size() scores for each event in the dataset.

Reimplemented in TrivialExpert, TMVAExpertMulticlass, and PythonExpert.

Definition at line 56 of file Expert.h.

◆ load()

void load ( Weightfile &  weightfile)
overridevirtual

Load the expert from a Weightfile.

Parameters
weightfilecontaining all information necessary to build the expert

Implements Expert.

Reimplemented in TMVAExpertRegression, TMVAExpertMulticlass, and TMVAExpertClassification.

Definition at line 385 of file TMVA.cc.

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