File rule_evaluation_example_wise.hpp

namespace boosting
class IExampleWiseRuleEvaluationFactory
#include <rule_evaluation_example_wise.hpp>

Defines an interface for all factories that allow to create instances of the type IRuleEvaluation that allow to calculate the predictions of rules, based on the gradients and Hessians that have been calculated according to a loss function that is applied example-wise.

Subclassed by boosting::ExampleWiseCompleteBinnedRuleEvaluationFactory, boosting::ExampleWiseCompleteRuleEvaluationFactory, boosting::ExampleWiseDynamicPartialBinnedRuleEvaluationFactory, boosting::ExampleWiseDynamicPartialRuleEvaluationFactory, boosting::ExampleWiseFixedPartialBinnedRuleEvaluationFactory, boosting::ExampleWiseFixedPartialRuleEvaluationFactory

Public Functions

inline virtual ~IExampleWiseRuleEvaluationFactory()
virtual std::unique_ptr<IRuleEvaluation<DenseExampleWiseStatisticVector>> create(const DenseExampleWiseStatisticVector &statisticVector, const CompleteIndexVector &indexVector) const = 0

Creates and returns a new object of type IRuleEvaluation that allows to calculate the predictions of rules that predict for all available labels, based on the gradients and Hessians that are stored by a DenseExampleWiseStatisticVector.

Parameters:

  • statisticVector – A reference to an object of type DenseExampleWiseStatisticVector. This vector is only used to identify the function that is able to deal with this particular type of vector via function overloading

  • indexVector – A reference to an object of type CompleteIndexVector that provides access to the indices of the labels for which the rules may predict

Returns:

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

virtual std::unique_ptr<IRuleEvaluation<DenseExampleWiseStatisticVector>> create(const DenseExampleWiseStatisticVector &statisticVector, const PartialIndexVector &indexVector) const = 0

Creates and returns a new object of type IRuleEvaluation that allows to calculate the predictions of rules that predict for a subset of the available labels, based on the gradients and Hessians that are stored by a DenseExampleWiseStatisticVector.

Parameters:

  • statisticVector – A reference to an object of type DenseExampleWiseStatisticVector. This vector is only used to identify the function that is able to deal with this particular type of vector via function overloading

  • indexVector – A reference to an object of type PartialIndexVector that provides access to the indices of the labels for which the rules may predict

Returns:

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