Expert Class Reference

Abstract base class of all Expert Each MVA library has its own implementation of this class, so all libraries can be accessed via this common interface. More...

#include <Expert.h>

Inheritance diagram for Expert:

Public Member Functions
	Expert ()=default
	Default constructor.
virtual void	load (Weightfile &weightfile)=0
	Load the expert from a Weightfile.
virtual std::vector< float >	apply (Dataset &test_data) const =0
	Apply this expert onto a dataset.
virtual std::vector< std::vector< float > >	applyMulticlass (Dataset &test_data) const
	Apply this m_expert onto a dataset.
virtual	~Expert ()=default
	Virtual destructor.

Protected Attributes
GeneralOptions	m_general_options
	General options loaded from the weightfile.

Detailed Description

Abstract base class of all Expert Each MVA library has its own implementation of this class, so all libraries can be accessed via this common interface.

Definition at line 31 of file Expert.h.

Member Function Documentation

apply()

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

pure virtual

Apply this expert onto a dataset.

Parameters

test_data

dataset

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

applyMulticlass()

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

inlinevirtual

Apply this m_expert onto a dataset.

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

Parameters

test_data

dataset.

Returns

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

Reimplemented in PythonExpert, TMVAExpertMulticlass, and TrivialExpert.

Definition at line 56 of file Expert.h.

      {
 
        B2ERROR("Attempted to call applyMulticlass() of the abstract base class MVA::Expert. All methods that support multiclass classification should override this definition.");
        (void) test_data;
 
        return std::vector<std::vector<float>>();
      };

load()

virtual void load ( Weightfile &  weightfile )

pure virtual

Load the expert from a Weightfile.

Parameters

weightfile

containing all information necessary to build the expert

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

Member Data Documentation

m_general_options

GeneralOptions m_general_options

protected

General options loaded from the weightfile.

Definition at line 70 of file Expert.h.

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

• mva/interface/include/Expert.h