File regression_matrix_row_wise.hpp

class IRowWiseRegressionMatrix : public IOutputMatrix
#include <regression_matrix_row_wise.hpp>

Defines an interface for all regression matrices that provide access to the ground truth regression scores of training examples.

Subclassed by ICContiguousRegressionMatrix, ICsrRegressionMatrix

Public Functions

inline virtual ~IRowWiseRegressionMatrix() override
virtual std::unique_ptr<IInstanceSampling> createInstanceSampling(const IRegressionInstanceSamplingFactory &factory, const SinglePartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0

Creates and returns a new instance of the class IInstanceSampling, based on the type of this regression matrix.

Parameters:

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

  • partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set

  • statistics – A reference to an object of type IStatistics that provides access to statistics about the quality of predictions for training examples

  • exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

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

virtual std::unique_ptr<IInstanceSampling> createInstanceSampling(const IRegressionInstanceSamplingFactory &factory, const SinglePartition &partition, IStatistics &statistics, const DenseWeightVector<float32> &exampleWeights) const = 0

Creates and returns a new instance of the class IInstanceSampling, based on the type of this regression matrix.

Parameters:

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

  • partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set

  • statistics – A reference to an object of type IStatistics that provides access to statistics about the quality of predictions for training examples

  • exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

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

virtual std::unique_ptr<IInstanceSampling> createInstanceSampling(const IRegressionInstanceSamplingFactory &factory, BiPartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0

Creates and returns a new instance of the class IInstanceSampling, based on the type of this regression matrix.

Parameters:

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

  • partition – 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, respectively

  • statistics – A reference to an object of type IStatistics that provides access to statistics about the quality of predictions for training examples

  • exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

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

virtual std::unique_ptr<IInstanceSampling> createInstanceSampling(const IRegressionInstanceSamplingFactory &factory, BiPartition &partition, IStatistics &statistics, const DenseWeightVector<float32> &exampleWeights) const = 0

Creates and returns a new instance of the class IInstanceSampling, based on the type of this regression matrix.

Parameters:

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

  • partition – 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, respectively

  • statistics – A reference to an object of type IStatistics that provides access to statistics about the quality of predictions for training examples

  • exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

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

virtual std::unique_ptr<IPartitionSampling> createPartitionSampling(const IRegressionPartitionSamplingFactory &factory) const = 0

Creates and returns a new instance of the class IPartitionSampling, based on the type of this regression matrix.

Parameters:

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

Returns:

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

virtual std::unique_ptr<IStatisticsProvider> createStatisticsProvider(const IRegressionStatisticsProviderFactory &factory) const = 0

Creates and returns a new instance of the class IStatisticsProvider, based on the type of this output matrix.

Parameters:

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

Returns:

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