File rule_model.hpp

class IRuleModel
#include <rule_model.hpp>

Defines an interface for all rule-based models.

Subclassed by IRuleList

Public Functions

inline virtual ~IRuleModel()
virtual uint32 getNumRules() const = 0

Returns the total number of rules in the model, including the default rule, if available.

Returns:

The number of rules

virtual uint32 getNumUsedRules() const = 0

Returns the number of used rules, including the default rule, if available.

Returns:

The number of used rules

virtual void setNumUsedRules(uint32 numUsedRules) = 0

Sets the number of used rules, including the default rule, if available.

Parameters:

numUsedRules – The number of used rules to be set or 0, if all rules should be used

virtual std::unique_ptr<IBinaryPredictor> createBinaryPredictor(const IBinaryPredictorFactory &factory, const CContiguousView<const float32> &featureMatrix, const IOutputSpaceInfo &outputSpaceInfo, 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 rule-based model.

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

  • outputSpaceInfo – A reference to an object of type IOutputSpaceInfo that provides information about the output space that may be used as a basis for making 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 IOutputSpaceInfo &outputSpaceInfo, 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 rule-based model.

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

  • outputSpaceInfo – A reference to an object of type IOutputSpaceInfo that provides information about the output space that may be used as a basis for making 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 IOutputSpaceInfo &outputSpaceInfo, 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 rule-based model.

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

  • outputSpaceInfo – A reference to an object of type IOutputSpaceInfo that provides information about the output space that may be used as a basis for making 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 IOutputSpaceInfo &outputSpaceInfo, 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 rule-based model.

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

  • outputSpaceInfo – A reference to an object of type IOutputSpaceInfo that provides information about the output space that may be used as a basis for making 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 IOutputSpaceInfo &outputSpaceInfo, uint32 numOutputs) const = 0

Creates and returns a new instance of the class IScorePredictor, based on the type of this rule-based model.

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

  • outputSpaceInfo – A reference to an object of type IOutputSpaceInfo that provides information about the output space that may be used as a basis for making 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 IOutputSpaceInfo &outputSpaceInfo, uint32 numOutputs) const = 0

Creates and returns a new instance of the class IScorePredictor, based on the type of this rule-based model.

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

  • outputSpaceInfo – A reference to an object of type IOutputSpaceInfo that provides information about the output space that may be used as a basis for making 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 IOutputSpaceInfo &outputSpaceInfo, 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 rule-based model.

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

  • outputSpaceInfo – A reference to an object of type IOutputSpaceInfo that provides information about the output space that may be used as a basis for making 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 IOutputSpaceInfo &outputSpaceInfo, 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 rule-based model.

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

  • outputSpaceInfo – A reference to an object of type IOutputSpaceInfo that provides information about the output space that may be used as a basis for making 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