CombinationExpert Class Reference

Expert for the Combination MVA method. More...

#include <Combination.h>

Inheritance diagram for CombinationExpert:

Collaboration diagram for CombinationExpert:

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 expert onto a dataset. More...
virtual std::vector< float >	apply (Dataset &test_data, const unsigned int classID) const
	Apply this expert onto a dataset. More...

Protected Attributes
GeneralOptions	m_general_options
	General options loaded from the weightfile.

Private Attributes
CombinationOptions	m_specific_options
	Method specific options.
std::vector< std::unique_ptr< Expert > >	m_experts
	Experts of the methods to combine.
std::vector< std::vector< std::string > >	m_expert_variables
	Results of the experts to combine.

Detailed Description

Expert for the Combination MVA method.

Definition at line 85 of file Combination.h.

Member Function Documentation

apply() [1/2]

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

overridevirtual

Apply this expert onto a dataset.

Parameters

test_data

dataset

Implements Expert.

Definition at line 115 of file Combination.cc.

                                                    {}, test_data);
        expert_probabilities.push_back(m_experts[iExpert]->apply(sub_dataset));
      }
 
      for (unsigned int iEvent = 0; iEvent < test_data.getNumberOfEvents(); ++iEvent) {
        double a = 1.0;
        double b = 1.0;
        for (unsigned int iExpert = 0; iExpert < m_experts.size(); ++iExpert) {
          a *= expert_probabilities[iExpert][iEvent];
          b *= (1.0 - expert_probabilities[iExpert][iEvent]);
        }
        probabilities[iEvent] = a / (a + b);
      }
      return probabilities;
    }
 
  }
}

apply() [2/2]

virtual std::vector<float> apply ( Dataset &  test_data, const unsigned int  classID  ) const

inlinevirtualinherited

Apply this expert onto a dataset.

Multi-class mode signature. Not pure virtual, since not all derived classes need to re-implement this.

Parameters

test_data	dataset
classID	class identifier.

Reimplemented in TMVAExpertMulticlass.

Definition at line 59 of file Expert.h.

      {
 
        (void) test_data;
        (void) classID;
 
        return std::vector<float>();
      };

load()

void load ( Weightfile &  weightfile )

overridevirtual

Load the expert from a Weightfile.

Parameters

weightfile

containing all information necessary to build the expert

Implements Expert.

Definition at line 87 of file Combination.cc.

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

• mva/methods/include/Combination.h
• mva/methods/src/Combination.cc