File statistics_provider_non_decomposable_dense.hpp¶

namespace boosting

template<typename StatisticType> class DenseNonDecomposableClassificationStatisticsProviderFactory : public IClassificationStatisticsProviderFactory ¶

#include <statistics_provider_non_decomposable_dense.hpp>

Allows to create instances of the class IStatisticsProvider that can be used in classification problems and provide access to an object of type INonDecomposableStatistics using dense data structures for storing the statistics.

Template Parameters:: StatisticType – The type of the statistics

Public Functions

DenseNonDecomposableClassificationStatisticsProviderFactory(std::unique_ptr<INonDecomposableClassificationLossFactory<StatisticType>> lossFactoryPtr, std::unique_ptr<IClassificationEvaluationMeasureFactory<StatisticType>> evaluationMeasureFactoryPtr, std::unique_ptr<INonDecomposableRuleEvaluationFactory> defaultRuleEvaluationFactoryPtr, std::unique_ptr<INonDecomposableRuleEvaluationFactory> regularRuleEvaluationFactoryPtr, std::unique_ptr<INonDecomposableRuleEvaluationFactory> pruningRuleEvaluationFactoryPtr, MultiThreadingSettings multiThreadingSettings)¶

Parameters:

lossFactoryPtr – An unique pointer to an object of type INonDecomposableClassificationLossFactory that allows to create implementations of the loss function that should be used for calculating gradients and Hessians
evaluationMeasureFactoryPtr – An unique pointer to an object of type IClassificationEvaluationMeasureFactory that allows to create implementations of the evaluation measure that should be used for assessing the quality of predictions
defaultRuleEvaluationFactoryPtr – An unique pointer to an object of type INonDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, of the default rule
regularRuleEvaluationFactoryPtr – An unique pointer to an object of type INonDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, of all remaining rules
pruningRuleEvaluationFactoryPtr – An unique pointer to an object of type INonDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, when pruning rules
multiThreadingSettings – An object of type MultiThreadingSettings that stores the settings to be used for calculating the initial statistics in parallel

std::unique_ptr<IStatisticsProvider> create(const CContiguousView<const uint8> &labelMatrix) const override¶

See also

IClassificationStatisticsProviderFactory::create

std::unique_ptr<IStatisticsProvider> create(const BinaryCsrView &labelMatrix) const override¶

See also

IClassificationStatisticsProviderFactory::create

Private Members

const std::unique_ptr<INonDecomposableClassificationLossFactory<StatisticType>> lossFactoryPtr_¶

const std::unique_ptr<IClassificationEvaluationMeasureFactory<StatisticType>> evaluationMeasureFactoryPtr_¶

const std::unique_ptr<INonDecomposableRuleEvaluationFactory> defaultRuleEvaluationFactoryPtr_¶

const std::unique_ptr<INonDecomposableRuleEvaluationFactory> regularRuleEvaluationFactoryPtr_¶

const std::unique_ptr<INonDecomposableRuleEvaluationFactory> pruningRuleEvaluationFactoryPtr_¶

const MultiThreadingSettings multiThreadingSettings_¶

template<typename StatisticType> class DenseNonDecomposableRegressionStatisticsProviderFactory : public IRegressionStatisticsProviderFactory ¶

#include <statistics_provider_non_decomposable_dense.hpp>

Allows to create instances of the class IStatisticsProvider that can be used in regression problems and provide access to an object of type INonDecomposableStatistics using dense data structures for storing the statistics.

Template Parameters:: StatisticType – The type of the statistics

Public Functions

DenseNonDecomposableRegressionStatisticsProviderFactory(std::unique_ptr<INonDecomposableRegressionLossFactory<StatisticType>> lossFactoryPtr, std::unique_ptr<IRegressionEvaluationMeasureFactory<StatisticType>> evaluationMeasureFactoryPtr, std::unique_ptr<INonDecomposableRuleEvaluationFactory> defaultRuleEvaluationFactoryPtr, std::unique_ptr<INonDecomposableRuleEvaluationFactory> regularRuleEvaluationFactoryPtr, std::unique_ptr<INonDecomposableRuleEvaluationFactory> pruningRuleEvaluationFactoryPtr, MultiThreadingSettings multiThreadingSettings)¶

Parameters:

lossFactoryPtr – An unique pointer to an object of type INonDecomposableRegressionLossFactory that allows to create implementations of the loss function that should be used for calculating gradients and Hessians
evaluationMeasureFactoryPtr – An unique pointer to an object of type IRegressionEvaluationMeasureFactory that allows to create implementations of the evaluation measure that should be used for assessing the quality of predictions
defaultRuleEvaluationFactoryPtr – An unique pointer to an object of type INonDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, of the default rule
regularRuleEvaluationFactoryPtr – An unique pointer to an object of type INonDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, of all remaining rules
pruningRuleEvaluationFactoryPtr – An unique pointer to an object of type INonDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, when pruning rules
multiThreadingSettings – An object of type MultiThreadingSettings that stores the settings to be used for calculating the initial statistics in parallel

std::unique_ptr<IStatisticsProvider> create(const CContiguousView<const float32> &regressionMatrix) const override¶

See also

IRegressionStatisticsProviderFactory::create

std::unique_ptr<IStatisticsProvider> create(const CsrView<const float32> &regressionMatrix) const override¶

See also

IRegressionStatisticsProviderFactory::create

Private Members

const std::unique_ptr<INonDecomposableRegressionLossFactory<StatisticType>> lossFactoryPtr_¶

const std::unique_ptr<IRegressionEvaluationMeasureFactory<StatisticType>> evaluationMeasureFactoryPtr_¶

const std::unique_ptr<INonDecomposableRuleEvaluationFactory> defaultRuleEvaluationFactoryPtr_¶

const std::unique_ptr<INonDecomposableRuleEvaluationFactory> regularRuleEvaluationFactoryPtr_¶

const std::unique_ptr<INonDecomposableRuleEvaluationFactory> pruningRuleEvaluationFactoryPtr_¶

const MultiThreadingSettings multiThreadingSettings_¶

template<typename StatisticType> class DenseConvertibleNonDecomposableClassificationStatisticsProviderFactory : public IClassificationStatisticsProviderFactory ¶

#include <statistics_provider_non_decomposable_dense.hpp>

Allows to create instances of the class IStatisticsProvider that provide access to an object of type INonDecomposableStatistics, which uses dense data structures to store the statistics and can be converted into an object of type IDecomposableStatistics.

Template Parameters:: StatisticType – The type of the statistics

Public Functions

DenseConvertibleNonDecomposableClassificationStatisticsProviderFactory(std::unique_ptr<INonDecomposableClassificationLossFactory<StatisticType>> lossFactoryPtr, std::unique_ptr<IClassificationEvaluationMeasureFactory<StatisticType>> evaluationMeasureFactoryPtr, std::unique_ptr<INonDecomposableRuleEvaluationFactory> defaultRuleEvaluationFactoryPtr, std::unique_ptr<IDecomposableRuleEvaluationFactory> regularRuleEvaluationFactoryPtr, std::unique_ptr<IDecomposableRuleEvaluationFactory> pruningRuleEvaluationFactoryPtr, MultiThreadingSettings multiThreadingSettings)¶

Parameters:

lossFactoryPtr – An unique pointer to an object of type INonDecomposableClassificationLossFactory that allows to create implementations of the loss function that should be used for calculating gradients and Hessians
evaluationMeasureFactoryPtr – An unique pointer to an object of type IClassificationEvaluationMeasureFactory that allows to create implementations of the evaluation measure that should be used for assessing the quality of predictions
defaultRuleEvaluationFactoryPtr – An unique pointer to an object of type INonDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, of the default rule
regularRuleEvaluationFactoryPtr – An unique pointer to an object of type IDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, of all remaining rules
pruningRuleEvaluationFactoryPtr – An unique pointer to an object of type IDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, when pruning rules
multiThreadingSettings – An object of type MultiThreadingSettings that stores the settings to be used for calculating the initial statistics in parallel

std::unique_ptr<IStatisticsProvider> create(const CContiguousView<const uint8> &labelMatrix) const override¶

See also

IClassificationStatisticsProviderFactory::create

std::unique_ptr<IStatisticsProvider> create(const BinaryCsrView &labelMatrix) const override¶

See also

IClassificationStatisticsProviderFactory::create

Private Members

const std::unique_ptr<INonDecomposableClassificationLossFactory<StatisticType>> lossFactoryPtr_¶

const std::unique_ptr<IClassificationEvaluationMeasureFactory<StatisticType>> evaluationMeasureFactoryPtr_¶

const std::unique_ptr<INonDecomposableRuleEvaluationFactory> defaultRuleEvaluationFactoryPtr_¶

const std::unique_ptr<IDecomposableRuleEvaluationFactory> regularRuleEvaluationFactoryPtr_¶

const std::unique_ptr<IDecomposableRuleEvaluationFactory> pruningRuleEvaluationFactoryPtr_¶

const MultiThreadingSettings multiThreadingSettings_¶

template<typename StatisticType> class DenseConvertibleNonDecomposableRegressionStatisticsProviderFactory : public IRegressionStatisticsProviderFactory ¶

#include <statistics_provider_non_decomposable_dense.hpp>

Template Parameters:: StatisticType – The type of the statistics

Public Functions

DenseConvertibleNonDecomposableRegressionStatisticsProviderFactory(std::unique_ptr<INonDecomposableRegressionLossFactory<StatisticType>> lossFactoryPtr, std::unique_ptr<IRegressionEvaluationMeasureFactory<StatisticType>> evaluationMeasureFactoryPtr, std::unique_ptr<INonDecomposableRuleEvaluationFactory> defaultRuleEvaluationFactoryPtr, std::unique_ptr<IDecomposableRuleEvaluationFactory> regularRuleEvaluationFactoryPtr, std::unique_ptr<IDecomposableRuleEvaluationFactory> pruningRuleEvaluationFactoryPtr, MultiThreadingSettings multiThreadingSettings)¶

Parameters:

lossFactoryPtr – An unique pointer to an object of type INonDecomposableRegressionLossFactory that allows to create implementations of the loss function that should be used for calculating gradients and Hessians
evaluationMeasureFactoryPtr – An unique pointer to an object of type IRegressionEvaluationMeasureFactory that allows to create implementations of the evaluation measure that should be used for assessing the quality of predictions
defaultRuleEvaluationFactoryPtr – An unique pointer to an object of type INonDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, of the default rule
regularRuleEvaluationFactoryPtr – An unique pointer to an object of type IDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, of all remaining rules
pruningRuleEvaluationFactoryPtr – An unique pointer to an object of type IDecomposableRuleEvaluationFactory that should be used for calculating the predictions, as well as corresponding quality scores, when pruning rules
multiThreadingSettings – An object of type MultiThreadingSettings that stores the settings to be used for calculating the initial statistics in parallel

std::unique_ptr<IStatisticsProvider> create(const CContiguousView<const float32> &regressionMatrix) const override¶

See also

IRegressionStatisticsProviderFactory::create

std::unique_ptr<IStatisticsProvider> create(const CsrView<const float32> &regressionMatrix) const override¶

See also

IRegressionStatisticsProviderFactory::create

Private Members

const std::unique_ptr<INonDecomposableRegressionLossFactory<StatisticType>> lossFactoryPtr_¶

const std::unique_ptr<IRegressionEvaluationMeasureFactory<StatisticType>> evaluationMeasureFactoryPtr_¶

const std::unique_ptr<INonDecomposableRuleEvaluationFactory> defaultRuleEvaluationFactoryPtr_¶

const std::unique_ptr<IDecomposableRuleEvaluationFactory> regularRuleEvaluationFactoryPtr_¶

const std::unique_ptr<IDecomposableRuleEvaluationFactory> pruningRuleEvaluationFactoryPtr_¶

const MultiThreadingSettings multiThreadingSettings_¶