File output_space_info.hpp

class IOutputSpaceInfo
#include <output_space_info.hpp>

Defines an interface for all classes that provide information about the output space that may be used as a basis for making predictions.

Subclassed by ILabelVectorSet, INoOutputSpaceInfo

Public Functions

inline virtual ~IOutputSpaceInfo()
virtual std::unique_ptr<IJointProbabilityCalibrator> createJointProbabilityCalibrator(const IJointProbabilityCalibratorFactory &factory, const IMarginalProbabilityCalibrationModel &marginalProbabilityCalibrationModel) const = 0

Creates and returns a new instance of the class IJointProbabilityCalibrator, based on the type of this information about the output space.

Parameters:
Returns:

An unique pointer to an object of type IJointProbabilityCalibrator that has been created

virtual std::unique_ptr<IBinaryPredictor> createBinaryPredictor(const IBinaryPredictorFactory &factory, const CContiguousView<const float32> &featureMatrix, const RuleList &model, const IMarginalProbabilityCalibrationModel &marginalProbabilityCalibrationModel, const IJointProbabilityCalibrationModel &jointProbabilityCalibrationModel, uint32 numLabels) const = 0

Creates and returns a new instance of the class IBinaryPredictor, based on the type of this information about the output space.

Parameters:

  • factory – A reference to an object of type IBinaryPredictorFactory that should be used to create the instance

  • featureMatrix – A reference to an object of type CContiguousView that provides row-wise access to the features of the query examples

  • model – A reference to an object of type RuleList that should be used to obtain predictions

  • marginalProbabilityCalibrationModel – A reference to an object of type IMarginalProbabilityCalibrationModel that may be used for the calibration of marginal probabilities

  • jointProbabilityCalibrationModel – A reference to an object of type IJointProbabilityCalibrationModel that may be used for the calibration of joint probabilities

  • numLabels – The number of labels to predict for

Returns:

An unique pointer to an object of type IBinaryPredictor that has been created

virtual std::unique_ptr<IBinaryPredictor> createBinaryPredictor(const IBinaryPredictorFactory &factory, const CsrView<const float32> &featureMatrix, const RuleList &model, const IMarginalProbabilityCalibrationModel &marginalProbabilityCalibrationModel, const IJointProbabilityCalibrationModel &jointProbabilityCalibrationModel, uint32 numLabels) const = 0

Creates and returns a new instance of the class IBinaryPredictor, based on the type of this information about the output space.

Parameters:

  • factory – A reference to an object of type IBinaryPredictorFactory that should be used to create the instance

  • featureMatrix – A reference to an object of type CsrView that provides row-wise access to the features of the query examples

  • model – A reference to an object of type RuleList that should be used to obtain predictions

  • marginalProbabilityCalibrationModel – A reference to an object of type IMarginalProbabilityCalibrationModel that may be used for the calibration of marginal probabilities

  • jointProbabilityCalibrationModel – A reference to an object of type IJointProbabilityCalibrationModel that may be used for the calibration of joint probabilities

  • numLabels – The number of labels to predict for

Returns:

An unique pointer to an object of type IBinaryPredictor that has been created

virtual std::unique_ptr<ISparseBinaryPredictor> createSparseBinaryPredictor(const ISparseBinaryPredictorFactory &factory, const CContiguousView<const float32> &featureMatrix, const RuleList &model, const IMarginalProbabilityCalibrationModel &marginalProbabilityCalibrationModel, const IJointProbabilityCalibrationModel &jointProbabilityCalibrationModel, uint32 numLabels) const = 0

Creates and returns a new instance of the class ISparseBinaryPredictor, based on the type of this information about the output space.

Parameters:

  • factory – A reference to an object of type ISparseBinaryPredictorFactory that should be used to create the instance

  • featureMatrix – A reference to an object of type CContiguousView that provides row-wise access to the features of the query examples

  • model – A reference to an object of type RuleList that should be used to obtain predictions

  • marginalProbabilityCalibrationModel – A reference to an object of type IMarginalProbabilityCalibrationModel that may be used for the calibration of marginal probabilities

  • jointProbabilityCalibrationModel – A reference to an object of type IJointProbabilityCalibrationModel that may be used for the calibration of joint probabilities

  • numLabels – The number of labels to predict for

Returns:

An unique pointer to an object of type ISparseBinaryPredictor that has been created

virtual std::unique_ptr<ISparseBinaryPredictor> createSparseBinaryPredictor(const ISparseBinaryPredictorFactory &factory, const CsrView<const float32> &featureMatrix, const RuleList &model, const IMarginalProbabilityCalibrationModel &marginalProbabilityCalibrationModel, const IJointProbabilityCalibrationModel &jointProbabilityCalibrationModel, uint32 numLabels) const = 0

Creates and returns a new instance of the class ISparseBinaryPredictor, based on the type of this information about the output space.

Parameters:

  • factory – A reference to an object of type ISparseBinaryPredictorFactory that should be used to create the instance

  • featureMatrix – A reference to an object of type CsrView that provides row-wise access to the features of the query examples

  • model – A reference to an object of type RuleList that should be used to obtain predictions

  • marginalProbabilityCalibrationModel – A reference to an object of type IMarginalProbabilityCalibrationModel that may be used for the calibration of marginal probabilities

  • jointProbabilityCalibrationModel – A reference to an object of type IJointProbabilityCalibrationModel that may be used for the calibration of joint probabilities

  • numLabels – The number of labels to predict for

Returns:

An unique pointer to an object of type ISparseBinaryPredictor that has been created

virtual std::unique_ptr<IScorePredictor> createScorePredictor(const IScorePredictorFactory &factory, const CContiguousView<const float32> &featureMatrix, const RuleList &model, uint32 numOutputs) const = 0

Creates and returns a new instance of the class IScorePredictor, based on the type of this information about the output space.

Parameters:

  • factory – A reference to an object of type IScorePredictorFactory that should be used to create the instance

  • featureMatrix – A reference to an object of type CContiguousView that provides row-wise access to the features of the query examples

  • model – A reference to an object of type RuleList that should be used to obtain predictions

  • numOutputs – The number of outputs to predict for

Returns:

An unique pointer to an object of type IScorePredictor that has been created

virtual std::unique_ptr<IScorePredictor> createScorePredictor(const IScorePredictorFactory &factory, const CsrView<const float32> &featureMatrix, const RuleList &model, uint32 numOutputs) const = 0

Creates and returns a new instance of the class IScorePredictor, based on the type of this information about the output space.

Parameters:

  • factory – A reference to an object of type IScorePredictorFactory that should be used to create the instance

  • featureMatrix – A reference to an object of type CsrView that provides row-wise access to the features of the query examples

  • model – A reference to an object of type RuleList that should be used to obtain predictions

  • numOutputs – The number of outputs to predict for

Returns:

An unique pointer to an object of type IScorePredictor that has been created

virtual std::unique_ptr<IProbabilityPredictor> createProbabilityPredictor(const IProbabilityPredictorFactory &factory, const CContiguousView<const float32> &featureMatrix, const RuleList &model, const IMarginalProbabilityCalibrationModel &marginalProbabilityCalibrationModel, const IJointProbabilityCalibrationModel &jointProbabilityCalibrationModel, uint32 numLabels) const = 0

Creates and returns a new instance of the class IProbabilityPredictor, based on the type of this information about the output space.

Parameters:

  • factory – A reference to an object of type IProbabilityPredictorFactory that should be used to create the instance

  • featureMatrix – A reference to an object of type CContiguousView that provides row-wise access to the features of the query examples

  • model – A reference to an object of type RuleList that should be used to obtain predictions

  • marginalProbabilityCalibrationModel – A reference to an object of type IMarginalProbabilityCalibrationModel that may be used for the calibration of marginal probabilities

  • jointProbabilityCalibrationModel – A reference to an object of type IJointProbabilityCalibrationModel that may be used for the calibration of joint probabilities

  • numLabels – The number of labels to predict for

Returns:

An unique pointer to an object of type IProbabilityPredictor that has been created

virtual std::unique_ptr<IProbabilityPredictor> createProbabilityPredictor(const IProbabilityPredictorFactory &factory, const CsrView<const float32> &featureMatrix, const RuleList &model, const IMarginalProbabilityCalibrationModel &marginalProbabilityCalibrationModel, const IJointProbabilityCalibrationModel &jointProbabilityCalibrationModel, uint32 numLabels) const = 0

Creates and returns a new instance of the class IProbabilityPredictor, based on the type of this information about the output space.

Parameters:

  • factory – A reference to an object of type IProbabilityPredictorFactory that should be used to create the instance

  • featureMatrix – A reference to an object of type CsrView that provides row-wise access to the features of the query examples

  • model – A reference to an object of type RuleList that should be used to obtain predictions

  • marginalProbabilityCalibrationModel – A reference to an object of type IMarginalProbabilityCalibrationModel that may be used for the calibration of marginal probabilities

  • jointProbabilityCalibrationModel – A reference to an object of type IJointProbabilityCalibrationModel that may be used for the calibration of joint probabilities

  • numLabels – The number of labels to predict for

Returns:

An unique pointer to an object of type IProbabilityPredictor that has been created