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

Expert for the TMVA Regression 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 override
 Apply this m_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

TMVAOptionsRegression specific_options
 Method specific options.
 
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 Regression MVA method.

Definition at line 362 of file TMVA.h.

Member Function Documentation

◆ apply()

std::vector< float > apply ( Dataset &  test_data) const
overridevirtual

Apply this m_expert onto a dataset.

Parameters
test_datadataset

Implements Expert.

Definition at line 542 of file TMVA.cc.

◆ 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 m_expert

Reimplemented from TMVAExpert.

Definition at line 476 of file TMVA.cc.

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