File predictor_probability_marginalized.hpp¶

namespace boosting¶

class IMarginalizedProbabilityPredictorConfig¶

#include <predictor_probability_marginalized.hpp>

Defines an interface for all classes that allow to configure a predictor that predicts label-wise probabilities for given query examples by marginalizing over the joint probabilities of known label vectors.

Subclassed by boosting::MarginalizedProbabilityPredictorConfig

Public Functions

inline virtual ~IMarginalizedProbabilityPredictorConfig()¶

virtual bool isProbabilityCalibrationModelUsed() const = 0¶

Returns whether a model for the calibration of probabilities is used, if available, or not.

Returns:: True, if a model for the calibration of probabilities is used, if available, false otherwise

virtual IMarginalizedProbabilityPredictorConfig &setUseProbabilityCalibrationModel(bool useProbabilityCalibrationModel) = 0¶

Sets whether a model for the calibration of probabilities should be used, if available, or not.

Parameters:: useProbabilityCalibrationModel – True, if a model for the calibration of probabilities should be used, if available, false otherwise
Returns:: A reference to an object of type IMarginalizedProbabilityPredictorConfig that allows further configuration of the predictor

class MarginalizedProbabilityPredictorConfig : public boosting::IMarginalizedProbabilityPredictorConfig, public IProbabilityPredictorConfig ¶

#include <predictor_probability_marginalized.hpp>

Allows to configure a predictor that predicts label-wise probabilities for given query examples by marginalizing over the joint probabilities of known label vectors.

Public Functions

MarginalizedProbabilityPredictorConfig(const std::unique_ptr<ILossConfig> &lossConfigPtr, const std::unique_ptr<IMultiThreadingConfig> &multiThreadingConfigPtr)¶

Parameters:

lossConfigPtr – A reference to an unique pointer that stores the configuration of the loss function
multiThreadingConfigPtr – A reference to an unique pointer that stores the configuration of the multi-threading behavior that should be used to predict for several query examples in parallel

virtual bool isProbabilityCalibrationModelUsed() const override¶

Returns whether a model for the calibration of probabilities is used, if available, or not.

Returns:: True, if a model for the calibration of probabilities is used, if available, false otherwise

virtual IMarginalizedProbabilityPredictorConfig &setUseProbabilityCalibrationModel(bool useProbabilityCalibrationModel) override¶

Sets whether a model for the calibration of probabilities should be used, if available, or not.

Parameters:: useProbabilityCalibrationModel – True, if a model for the calibration of probabilities should be used, if available, false otherwise
Returns:: A reference to an object of type IMarginalizedProbabilityPredictorConfig that allows further configuration of the predictor

std::unique_ptr<IProbabilityPredictorFactory> createPredictorFactory(const IRowWiseFeatureMatrix &featureMatrix, uint32 numLabels) const override¶