File label_matrix_row_wise.hpp¶
-
class IRowWiseLabelMatrix : public ILabelMatrix¶
- #include <label_matrix_row_wise.hpp>
Defines an interface for all label matrices that provide access to the labels of the training examples.
Subclassed by ICContiguousLabelMatrix, ICsrLabelMatrix
Public Functions
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inline virtual ~IRowWiseLabelMatrix() override¶
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virtual float32 calculateLabelCardinality() const = 0¶
Calculates and returns the label cardinality, i.e., the average number of relevant labels per example.
- Returns:
The label cardinality
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virtual std::unique_ptr<LabelVector> createLabelVector(uint32 row) const = 0¶
Creates and returns a label vector that corresponds to a specific row in the label matrix.
- Parameters:
row – The row
- Returns:
An unique pointer to an object of type
LabelVector
that has been created
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virtual std::unique_ptr<IStatisticsProvider> createStatisticsProvider(const IStatisticsProviderFactory &factory) const = 0¶
Creates and returns a new instance of the class
IStatisticsProvider
, based on the type of this label matrix.- Parameters:
factory – A reference to an object of type
IStatisticsProviderFactory
that should be used to create the instance- Returns:
An unique pointer to an object of type
IStatisticsProvider
that has been created
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virtual std::unique_ptr<IPartitionSampling> createPartitionSampling(const IPartitionSamplingFactory &factory) const = 0¶
Creates and returns a new instance of the class
IPartitionSampling
, based on the type of this label matrix.- Parameters:
factory – A reference to an object of type
IPartitionSamplingFactory
that should be used to create the instance- Returns:
An unique pointer to an object of type
IPartitionSampling
that has been created
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virtual std::unique_ptr<IInstanceSampling> createInstanceSampling(const IInstanceSamplingFactory &factory, const SinglePartition &partition, IStatistics &statistics) const = 0¶
Creates and returns a new instance of the class
IInstanceSampling
, based on the type of this label matrix.- Parameters:
factory – A reference to an object of type
IInstanceSamplingFactory
that should be used to create the instancepartition – A reference to an object of type
SinglePartition
that provides access to the indices of the training examples that are included in the training setstatistics – A reference to an object of type
IStatistics
that provides access to the statistics which serve as a basis for learning rules
- Returns:
An unique pointer to an object of type
IInstanceSampling
that has been created
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virtual std::unique_ptr<IInstanceSampling> createInstanceSampling(const IInstanceSamplingFactory &factory, BiPartition &partition, IStatistics &statistics) const = 0¶
Creates and returns a new instance of the class
IInstanceSampling
, based on the type of this label matrix.- Parameters:
factory – A reference to an object of type
IInstanceSamplingFactory
that should be used to create the instancepartition – A reference to an object of type
BiPartition
that provides access to the indices of the training examples that are included in the training set and the holdout set, respectivelystatistics – A reference to an object of type
IStatistics
that provides access to the statistics which serve as a basis for learning rules
- Returns:
An unique pointer to an object of type
IInstanceSampling
that has been created
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virtual std::unique_ptr<IMarginalProbabilityCalibrationModel> fitMarginalProbabilityCalibrationModel(const IMarginalProbabilityCalibrator &probabilityCalibrator, const SinglePartition &partition, const IStatistics &statistics) const = 0¶
Fits and returns a model for the calibration of marginal probabilities, based on the type of this label matrix.
- Parameters:
probabilityCalibrator – A reference to an object of type
IMarginalProbabilityCalibrator
that should be used to fit the calibration modelpartition – A reference to an object of type
SinglePartition
that provides access to the indices of the training examples that are included in the training setstatistics – A reference to an object of type
IStatistics
that provides access to statistics about the labels of the training examples
- Returns:
An unique pointer to an object of type
IMarginalProbabilityCalibrationModel
that has been fit
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virtual std::unique_ptr<IMarginalProbabilityCalibrationModel> fitMarginalProbabilityCalibrationModel(const IMarginalProbabilityCalibrator &probabilityCalibrator, BiPartition &partition, const IStatistics &statistics) const = 0¶
Fits and returns a model for the calibration of marginal probabilities, based on the type of this label matrix.
- Parameters:
probabilityCalibrator – A reference to an object of type
IMarginalProbabilityCalibrator
that should be used to fit the calibration modelpartition – A reference to an object of type
BiPartition
that provides access to the indices of the training examples that are included in the training set and the holdout set, respectivelystatistics – A reference to an object of type
IStatistics
that provides access to statistics about the labels of the training examples
- Returns:
An unique pointer to an object of type
IMarginalProbabilityCalibrationModel
that has been fit
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virtual std::unique_ptr<IJointProbabilityCalibrationModel> fitJointProbabilityCalibrationModel(const IJointProbabilityCalibrator &probabilityCalibrator, const SinglePartition &partition, const IStatistics &statistics) const = 0¶
Fits and returns a model for the calibration of joint probabilities, based on the type of this label matrix.
- Parameters:
probabilityCalibrator – A reference to an object of type
IJointProbabilityCalibrator
that should be used to fit the calibration modelpartition – A reference to an object of type
SinglePartition
that provides access to the indices of the training examples that are included in the training setstatistics – A reference to an object of type
IStatistics
that provides access to statistics about the labels of the training examples
- Returns:
An unique pointer to an object of type
IJointProbabilityCalibrationModel
that has been fit
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virtual std::unique_ptr<IJointProbabilityCalibrationModel> fitJointProbabilityCalibrationModel(const IJointProbabilityCalibrator &probabilityCalibrator, BiPartition &partition, const IStatistics &statistics) const = 0¶
Fits and returns a model for the calibration of joint probabilities, based on the type of this label matrix.
- Parameters:
probabilityCalibrator – A reference to an object of type
IJointProbabilityCalibrator
that should be used to fit the calibration modelpartition – A reference to an object of type
BiPartition
that provides access to the indices of the training examples that are included in the training set and the holdout set, respectivelystatistics – A reference to an object of type
IStatistics
that provides access to statistics about the labels of the training examples
- Returns:
An unique pointer to an object of type
IJointProbabilityCalibrationModel
that has been fit
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inline virtual ~IRowWiseLabelMatrix() override¶