File loss_label_wise_sparse.hpp

namespace boosting
class ISparseLabelWiseLoss : public virtual boosting::ILabelWiseLoss, public ISparseEvaluationMeasure
#include <loss_label_wise_sparse.hpp>

Defines an interface for all (decomposable) loss functions that are applied label-wise and are suited for the use of sparse data structures. To meet this requirement, the gradients and Hessians that are computed by the loss function should be zero, if the prediction for a label is correct.

Public Functions

inline virtual ~ISparseLabelWiseLoss() override
virtual void updateLabelWiseStatistics(uint32 exampleIndex, const CContiguousView<const uint8> &labelMatrix, const SparseSetView<float64> &scoreMatrix, CompleteIndexVector::const_iterator labelIndicesBegin, CompleteIndexVector::const_iterator labelIndicesEnd, SparseSetView<Tuple<float64>> &statisticView) const = 0

Updates the statistics of the example at a specific index, considering only the labels, whose indices are provided by a CompleteIndexVector.

Parameters:

  • exampleIndex – The index of the example for which the gradients and Hessians should be updated

  • labelMatrix – A reference to an object of type CContiguousView that provides random access to the labels of the training examples

  • scoreMatrix – A reference to an object of type SparseSetView that stores the currently predicted scores

  • labelIndicesBegin – A CompleteIndexVector::const_iterator to the beginning of the label indices

  • labelIndicesEnd – A CompleteIndexVector::const_iterator to the end of the label indices

  • statisticView – A reference to an object of type SparseSetView to be updated

virtual void updateLabelWiseStatistics(uint32 exampleIndex, const CContiguousView<const uint8> &labelMatrix, const SparseSetView<float64> &scoreMatrix, PartialIndexVector::const_iterator labelIndicesBegin, PartialIndexVector::const_iterator labelIndicesEnd, SparseSetView<Tuple<float64>> &statisticView) const = 0

Updates the statistics of the example at a specific index, considering only the labels, whose indices are provided by a PartialIndexVector.

Parameters:

  • exampleIndex – The index of the example for which the gradients and Hessians should be updated

  • labelMatrix – A reference to an object of type CContiguousView that provides random access to the labels of the training examples

  • scoreMatrix – A reference to an object of type SparseSetView that stores the currently predicted scores

  • labelIndicesBegin – A PartialIndexVector::const_iterator to the beginning of the label indices

  • labelIndicesEnd – A PartialIndexVector::const_iterator to the end of the label indices

  • statisticView – A reference to an object of type SparseSetView to be updated

virtual void updateLabelWiseStatistics(uint32 exampleIndex, const BinaryCsrView &labelMatrix, const SparseSetView<float64> &scoreMatrix, CompleteIndexVector::const_iterator labelIndicesBegin, CompleteIndexVector::const_iterator labelIndicesEnd, SparseSetView<Tuple<float64>> &statisticView) const = 0

Updates the statistics of the example at a specific index, considering only the labels, whose indices are provided by a CompleteIndexVector.

Parameters:

  • exampleIndex – The index of the example for which the gradients and Hessians should be updated

  • labelMatrix – A reference to an object of type BinaryCsrView that provides row-wise access to the labels of the training examples

  • scoreMatrix – A reference to an object of type SparseSetView that stores the currently predicted scores

  • labelIndicesBegin – A CompleteIndexVector::const_iterator to the beginning of the label indices

  • labelIndicesEnd – A CompleteIndexVector::const_iterator to the end of the label indices

  • statisticView – A reference to an object of type SparseSetView to be updated

virtual void updateLabelWiseStatistics(uint32 exampleIndex, const BinaryCsrView &labelMatrix, const SparseSetView<float64> &scoreMatrix, PartialIndexVector::const_iterator labelIndicesBegin, PartialIndexVector::const_iterator labelIndicesEnd, SparseSetView<Tuple<float64>> &statisticView) const = 0

Updates the statistics of the example at a specific index, considering only the labels, whose indices are provided by a PartialIndexVector.

Parameters:

  • exampleIndex – The index of the example for which the gradients and Hessians should be updated

  • labelMatrix – A reference to an object of type BinaryCsrView that provides row-wise access to the labels of the training examples

  • scoreMatrix – A reference to an object of type SparseSetView that stores the currently predicted scores

  • labelIndicesBegin – A PartialIndexVector::const_iterator to the beginning of the label indices

  • labelIndicesEnd – A PartialIndexVector::const_iterator to the end of the label indices

  • statisticView – A reference to an object of type SparseSetView to be updated

void updateLabelWiseStatistics(uint32 exampleIndex, const CContiguousView<const uint8> &labelMatrix, const CContiguousView<float64> &scoreMatrix, CompleteIndexVector::const_iterator labelIndicesBegin, CompleteIndexVector::const_iterator labelIndicesEnd, CContiguousView<Tuple<float64>> &statisticView) const = 0

Updates the statistics of the example at a specific index, considering only the labels, whose indices are provided by a CompleteIndexVector.

Parameters:

  • exampleIndex – The index of the example for which the gradients and Hessians should be updated

  • labelMatrix – A reference to an object of type CContiguousView that provides random access to the labels of the training examples

  • scoreMatrix – A reference to an object of type CContiguousView that stores the currently predicted scores

  • labelIndicesBegin – A CompleteIndexVector::const_iterator to the beginning of the label indices

  • labelIndicesEnd – A CompleteIndexVector::const_iterator to the end of the label indices

  • statisticView – A reference to an object of type CContiguousView to be updated

void updateLabelWiseStatistics(uint32 exampleIndex, const CContiguousView<const uint8> &labelMatrix, const CContiguousView<float64> &scoreMatrix, PartialIndexVector::const_iterator labelIndicesBegin, PartialIndexVector::const_iterator labelIndicesEnd, CContiguousView<Tuple<float64>> &statisticView) const = 0

Updates the statistics of the example at a specific index, considering only the labels, whose indices are provided by a PartialIndexVector.

Parameters:

  • exampleIndex – The index of the example for which the gradients and Hessians should be updated

  • labelMatrix – A reference to an object of type CContiguousView that provides random access to the labels of the training examples

  • scoreMatrix – A reference to an object of type CContiguousView that stores the currently predicted scores

  • labelIndicesBegin – A PartialIndexVector::const_iterator to the beginning of the label indices

  • labelIndicesEnd – A PartialIndexVector::const_iterator to the end of the label indices

  • statisticView – A reference to an object of type CContiguousView to be updated

void updateLabelWiseStatistics(uint32 exampleIndex, const BinaryCsrView &labelMatrix, const CContiguousView<float64> &scoreMatrix, CompleteIndexVector::const_iterator labelIndicesBegin, CompleteIndexVector::const_iterator labelIndicesEnd, CContiguousView<Tuple<float64>> &statisticView) const = 0

Updates the statistics of the example at a specific index, considering only the labels, whose indices are provided by a CompleteIndexVector.

Parameters:

  • exampleIndex – The index of the example for which the gradients and Hessians should be updated

  • labelMatrix – A reference to an object of type BinaryCsrView that provides row-wise access to the labels of the training examples

  • scoreMatrix – A reference to an object of type CContiguousView that stores the currently predicted scores

  • labelIndicesBegin – A CompleteIndexVector::const_iterator to the beginning of the label indices

  • labelIndicesEnd – A CompleteIndexVector::const_iterator to the end of the label indices

  • statisticView – A reference to an object of type CContiguousView to be updated

void updateLabelWiseStatistics(uint32 exampleIndex, const BinaryCsrView &labelMatrix, const CContiguousView<float64> &scoreMatrix, PartialIndexVector::const_iterator labelIndicesBegin, PartialIndexVector::const_iterator labelIndicesEnd, CContiguousView<Tuple<float64>> &statisticView) const = 0

Updates the statistics of the example at a specific index, considering only the labels, whose indices are provided by a PartialIndexVector.

Parameters:

  • exampleIndex – The index of the example for which the gradients and Hessians should be updated

  • labelMatrix – A reference to an object of type BinaryCsrView that provides row-wise access to the labels of the training examples

  • scoreMatrix – A reference to an object of type CContiguousView that stores the currently predicted scores

  • labelIndicesBegin – A PartialIndexVector::const_iterator to the beginning of the label indices

  • labelIndicesEnd – A PartialIndexVector::const_iterator to the end of the label indices

  • statisticView – A reference to an object of type CContiguousView to be updated

class ISparseLabelWiseLossFactory : public boosting::ILabelWiseLossFactory, public ISparseEvaluationMeasureFactory
#include <loss_label_wise_sparse.hpp>

Defines an interface for all factories that allow to create instances of the type ISparseLabelWiseLoss.

Public Functions

inline virtual ~ISparseLabelWiseLossFactory() override
virtual std::unique_ptr<ISparseLabelWiseLoss> createSparseLabelWiseLoss() const = 0

Creates and returns a new object of type ISparseLabelWiseLoss.

Returns:

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

inline virtual std::unique_ptr<ILabelWiseLoss> createLabelWiseLoss() const final override

See also

ILabelWiseLossFactory::createLabelWiseLoss

inline std::unique_ptr<ISparseEvaluationMeasure> createSparseEvaluationMeasure() const final override

See also

ISparseEvaluationMeasureFactory::createSparseEvaluationMeasure

class ISparseLabelWiseLossConfig : public boosting::ILabelWiseLossConfig
#include <loss_label_wise_sparse.hpp>

Defines an interface for all classes that allow to configure a (decomposable) loss function that is applied label-wise and is suited for the use of sparse data structures.

Subclassed by boosting::LabelWiseSquaredHingeLossConfig

Public Functions

inline virtual ~ISparseLabelWiseLossConfig() override
virtual std::unique_ptr<ISparseLabelWiseLossFactory> createSparseLabelWiseLossFactory() const = 0

Creates and returns a new object of type ISparseLabelWiseLossFactory according to the specified configuration.

Returns:

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

inline std::unique_ptr<ISparseEvaluationMeasureFactory> createSparseEvaluationMeasureFactory() const

Creates and returns a new object of type ISparseEvaluationMeasureFactory according to the specified configuration.

Returns:

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

inline virtual std::unique_ptr<ILabelWiseLossFactory> createLabelWiseLossFactory() const final override

Creates and returns a new object of type ILabelWiseLossFactory according to the specified configuration.

Returns:

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

inline virtual bool isSparse() const final override

Returns whether the loss function supports to use a sparse format for storing statistics or not.

Returns:

True, if the loss function supports to use a sparse format for storing statistics, false otherwise