Dataset needed during the training of a regression method. More...

#include <Regression.h>

Inheritance diagram for RegressionDataSet:

Collaboration diagram for RegressionDataSet:

[legend]

Public Member Functions
	RegressionDataSet (const GeneralOptions &general_options, Dataset *dataSet, double cutValue)
	Create a new regression data set out of the general options, a pointer to the real dataset and the cut value.

unsigned int	getNumberOfFeatures () const override
	Return the number of features from the real dataset.

unsigned int	getNumberOfEvents () const override
	Return the number of events from the real dataset.

unsigned int	getNumberOfSpectators () const override
	Return the number of spectators from the real dataset.

void	loadEvent (unsigned int iEvent) override
	Load an event. Sets all internal variables and sets the isSignal variable dependent on the cut value.

std::vector< float >	getFeature (unsigned int iFeature) override
	Return a specific feature from the real dataset.

std::vector< float >	getSpectator (unsigned int iSpectator) override
	Return a specific spectator from the real dataset.

std::vector< float >	getWeights () override
	Return the weights from the real dataset.

std::vector< float >	getTargets () override
	Return the targets from the real dataset.

virtual float	getSignalFraction ()
	Returns the signal fraction of the whole sample.

virtual unsigned int	getFeatureIndex (const std::string &feature)
	Return index of feature with the given name.

virtual unsigned int	getSpectatorIndex (const std::string &spectator)
	Return index of spectator with the given name.

virtual std::vector< bool >	getSignals ()
	Returns all is Signals.

Public Attributes
GeneralOptions	m_general_options
	GeneralOptions passed to this dataset.

std::vector< float >	m_input
	Contains all feature values of the currently loaded event.

std::vector< float >	m_spectators
	Contains all spectators values of the currently loaded event.

float	m_weight
	Contains the weight of the currently loaded event.

float	m_target
	Contains the target value of the currently loaded event.

bool	m_isSignal
	Defines if the currently loaded event is signal or background.

Private Attributes
double	m_cutValue
	The cut value.

Dataset *	m_childDataSet
	The real data set (our child)

Detailed Description

Dataset needed during the training of a regression method.

It basically wraps another dataset it receives as pointer and every call to this dataset is forwarded to the other dataset.

The only difference is, that the isSignal variable is set dependent on the cut value given in the constructor to

 isSignal = target >= cutValue

to generate a binary classification out of a regression task.

Definition at line 77 of file Regression.h.

Constructor & Destructor Documentation

◆ RegressionDataSet()

RegressionDataSet	(	const GeneralOptions &	general_options,
		Dataset *	dataSet,
		double	cutValue
	)

Create a new regression data set out of the general options, a pointer to the real dataset and the cut value.

Definition at line 16 of file Regression.cc.

                                                                                                             :
  Dataset(general_options), m_cutValue(cutValue), m_childDataSet(dataset)
{
}

Member Function Documentation

◆ getFeature()

std::vector< float > getFeature ( unsigned int iFeature )

overridevirtual

Return a specific feature from the real dataset.

Reimplemented from Dataset.

Definition at line 46 of file Regression.cc.

{
  return m_childDataSet->getFeature(iFeature);
}

◆ getFeatureIndex()

unsigned int getFeatureIndex ( const std::string & feature )

virtualinherited

Return index of feature with the given name.

Parameters

feature name of the feature

Definition at line 50 of file Dataset.cc.

    {
 
      auto it = std::find(m_general_options.m_variables.begin(), m_general_options.m_variables.end(), feature);
      if (it == m_general_options.m_variables.end()) {
        B2ERROR("Unknown feature named " << feature);
        return 0;
      }
      return std::distance(m_general_options.m_variables.begin(), it);
 
    }

◆ getNumberOfEvents()

unsigned int getNumberOfEvents ( ) const

overridevirtual

Return the number of events from the real dataset.

Implements Dataset.

Definition at line 36 of file Regression.cc.

{
  return m_childDataSet->getNumberOfEvents();
}

◆ getNumberOfFeatures()

unsigned int getNumberOfFeatures ( ) const

overridevirtual

Return the number of features from the real dataset.

Implements Dataset.

Definition at line 31 of file Regression.cc.

{
  return m_childDataSet->getNumberOfFeatures();
}

◆ getNumberOfSpectators()

unsigned int getNumberOfSpectators ( ) const

overridevirtual

Return the number of spectators from the real dataset.

Implements Dataset.

Definition at line 41 of file Regression.cc.

{
  return m_childDataSet->getNumberOfSpectators();
}

◆ getSignalFraction()

float getSignalFraction ( )

virtualinherited

Returns the signal fraction of the whole sample.

Reimplemented in SPlotDataset.

Definition at line 35 of file Dataset.cc.

    {
 
      double signal_weight_sum = 0;
      double weight_sum = 0;
      for (unsigned int i = 0; i < getNumberOfEvents(); ++i) {
        loadEvent(i);
        weight_sum += m_weight;
        if (m_isSignal)
          signal_weight_sum += m_weight;
      }
      return signal_weight_sum / weight_sum;
 
    }

◆ getSignals()

std::vector< bool > getSignals ( )

virtualinherited

Returns all is Signals.

Reimplemented in ReweightingDataset.

Definition at line 122 of file Dataset.cc.

    {
 
      std::vector<bool> result(getNumberOfEvents());
      for (unsigned int iEvent = 0; iEvent < getNumberOfEvents(); ++iEvent) {
        loadEvent(iEvent);
        result[iEvent] = m_isSignal;
      }
      return result;
 
    }

◆ getSpectator()

std::vector< float > getSpectator ( unsigned int iSpectator )

overridevirtual

Return a specific spectator from the real dataset.

Reimplemented from Dataset.

Definition at line 51 of file Regression.cc.

{
  return m_childDataSet->getSpectator(iSpectator);
}

◆ getSpectatorIndex()

unsigned int getSpectatorIndex ( const std::string & spectator )

virtualinherited

Return index of spectator with the given name.

Parameters

spectator name of the spectator

Definition at line 62 of file Dataset.cc.

    {
 
      auto it = std::find(m_general_options.m_spectators.begin(), m_general_options.m_spectators.end(), spectator);
      if (it == m_general_options.m_spectators.end()) {
        B2ERROR("Unknown spectator named " << spectator);
        return 0;
      }
      return std::distance(m_general_options.m_spectators.begin(), it);
 
    }

◆ getTargets()

std::vector< float > getTargets ( )

overridevirtual

Return the targets from the real dataset.

Reimplemented from Dataset.

Definition at line 61 of file Regression.cc.

{
  return m_childDataSet->getTargets();
}

◆ getWeights()

std::vector< float > getWeights ( )

overridevirtual

Return the weights from the real dataset.

Reimplemented from Dataset.

Definition at line 56 of file Regression.cc.

{
  return m_childDataSet->getWeights();
}

◆ loadEvent()

void loadEvent ( unsigned int iEvent )

overridevirtual

Load an event. Sets all internal variables and sets the isSignal variable dependent on the cut value.

Implements Dataset.

Definition at line 21 of file Regression.cc.

{
  m_childDataSet->loadEvent(iEvent);
  m_input = m_childDataSet->m_input;
  m_spectators = m_childDataSet->m_spectators;
  m_isSignal = m_childDataSet->m_target >= m_cutValue;
  m_target = m_childDataSet->m_target;
  m_weight = m_childDataSet->m_weight;
}

Member Data Documentation

◆ m_childDataSet

Dataset* m_childDataSet

private

The real data set (our child)

Definition at line 111 of file Regression.h.

◆ m_cutValue

double m_cutValue

private

The cut value.

Definition at line 108 of file Regression.h.

◆ m_general_options

GeneralOptions m_general_options

inherited

GeneralOptions passed to this dataset.

Definition at line 122 of file Dataset.h.

◆ m_input

std::vector<float> m_input

inherited

Contains all feature values of the currently loaded event.

Definition at line 123 of file Dataset.h.

◆ m_isSignal

bool m_isSignal

inherited

Defines if the currently loaded event is signal or background.

Definition at line 127 of file Dataset.h.

◆ m_spectators

std::vector<float> m_spectators

inherited

Contains all spectators values of the currently loaded event.

Definition at line 124 of file Dataset.h.

◆ m_target

float m_target

inherited

Contains the target value of the currently loaded event.

Definition at line 126 of file Dataset.h.

◆ m_weight

float m_weight

inherited

Contains the weight of the currently loaded event.

Definition at line 125 of file Dataset.h.

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

mva/methods/include/Regression.h
mva/methods/src/Regression.cc

Public Member Functions

Public Attributes

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ RegressionDataSet()

Member Function Documentation

◆ getFeature()

◆ getFeatureIndex()

◆ getNumberOfEvents()

◆ getNumberOfFeatures()

◆ getNumberOfSpectators()

◆ getSignalFraction()

◆ getSignals()

◆ getSpectator()

◆ getSpectatorIndex()

◆ getTargets()

◆ getWeights()

◆ loadEvent()

Member Data Documentation

◆ m_childDataSet

◆ m_cutValue

◆ m_general_options

◆ m_input

◆ m_isSignal

◆ m_spectators

◆ m_target

◆ m_weight