9#include <mva/methods/Regression.h>
std::vector< float > m_spectators
Contains all spectators values of the currently loaded event.
std::vector< float > m_input
Contains all feature values of the currently loaded event.
Dataset(const GeneralOptions &general_options)
Constructs a new dataset given the general options.
bool m_isSignal
Defines if the currently loaded event is signal or background.
float m_weight
Contains the weight of the currently loaded event.
float m_target
Contains the target value of the currently loaded event.
General options which are shared by all MVA trainings.
std::vector< float > getTargets() override
Return the targets from the real dataset.
unsigned int getNumberOfEvents() const override
Return the number of events from the real dataset.
std::vector< float > getSpectator(unsigned int iSpectator) override
Return a specific spectator from the real dataset.
unsigned int getNumberOfSpectators() const override
Return the number of spectators from the real dataset.
unsigned int getNumberOfFeatures() const override
Return the number of features from the real dataset.
std::vector< float > getFeature(unsigned int iFeature) override
Return a specific feature from the real dataset.
std::vector< float > getWeights() override
Return the weights 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.
Dataset * m_childDataSet
The real data set (our child)
double m_cutValue
The cut value.
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 cu...
Abstract base class for different kinds of events.