File rule_evaluation_example_wise_complete_binned.hpp¶
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namespace boosting
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class ExampleWiseCompleteBinnedRuleEvaluationFactory : public boosting::IExampleWiseRuleEvaluationFactory¶
- #include <rule_evaluation_example_wise_complete_binned.hpp>
Allows to create instances of the class
IExampleWiseRuleEvaluationFactory
that allow to calculate the predictions of complete rules, which predict for all available labels, using gradient-based label binning.Public Functions
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ExampleWiseCompleteBinnedRuleEvaluationFactory(float64 l1RegularizationWeight, float64 l2RegularizationWeight, std::unique_ptr<ILabelBinningFactory> labelBinningFactoryPtr, const Blas &blas, const Lapack &lapack)¶
- Parameters:
l1RegularizationWeight – The weight of the L1 regularization that is applied for calculating the scores to be predicted by rules
l2RegularizationWeight – The weight of the L2 regularization that is applied for calculating the scores to be predicted by rules
labelBinningFactoryPtr – An unique pointer to an object of type
ILabelBinningFactory
that allows to create the implementation to be used to assign labels to binsblas – A reference to an object of type
Blas
that allows to execute BLAS routineslapack – A reference to an object of type
Lapack
that allows to execute LAPACK routines
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virtual std::unique_ptr<IRuleEvaluation<DenseExampleWiseStatisticVector>> create(const DenseExampleWiseStatisticVector &statisticVector, const CompleteIndexVector &indexVector) const override¶
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 aDenseExampleWiseStatisticVector
.- 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 overloadingindexVector – 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
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virtual std::unique_ptr<IRuleEvaluation<DenseExampleWiseStatisticVector>> create(const DenseExampleWiseStatisticVector &statisticVector, const PartialIndexVector &indexVector) const override¶
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 aDenseExampleWiseStatisticVector
.- 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 overloadingindexVector – 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
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ExampleWiseCompleteBinnedRuleEvaluationFactory(float64 l1RegularizationWeight, float64 l2RegularizationWeight, std::unique_ptr<ILabelBinningFactory> labelBinningFactoryPtr, const Blas &blas, const Lapack &lapack)¶
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class ExampleWiseCompleteBinnedRuleEvaluationFactory : public boosting::IExampleWiseRuleEvaluationFactory¶