Uses of Class
org.drip.measure.continuous.RdR1Distribution

Packages that use RdR1Distribution

Package	Description
org.drip.learning.regularization	Statistical Learning Empirical Loss Regularizer
org.drip.learning.rxtor1	Statistical Learning Empirical Loss Penalizer

Uses of RdR1Distribution in org.drip.learning.regularization

Methods in org.drip.learning.regularization with parameters of type RdR1Distribution

Modifier and Type	Method	Description
double	RegularizerRdCombinatorialToR1Continuous.structuralRisk(RdR1Distribution distRdR1, RdToR1 funcRdToR1, double[][] aadblX, double[] adblY)
double	RegularizerRdContinuousToR1Continuous.structuralRisk(RdR1Distribution distRdR1, RdToR1 funcRdToR1, double[][] aadblX, double[] adblY)
double	RegularizerRdToR1.structuralRisk(RdR1Distribution distRdR1, RdToR1 funcRdToR1, double[][] aadblX, double[] adblY)	Compute the Regularization Sample Structural Loss

Uses of RdR1Distribution in org.drip.learning.rxtor1

Methods in org.drip.learning.rxtor1 with parameters of type RdR1Distribution

Modifier and Type	Method	Description
double	EmpiricalLearningMetricEstimator.empiricalRisk(RdR1Distribution distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)	Compute the Empirical Sample Risk
double	L1LossLearner.empiricalRisk(RdR1Distribution distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
double	LipschitzLossLearner.empiricalRisk(RdR1Distribution distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
double	LpLossLearner.empiricalRisk(RdR1Distribution distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
double	EmpiricalLearningMetricEstimator.regularizedRisk(RdR1Distribution distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)	Compute the Regularized Sample Risk (Empirical + Structural)
double	GeneralizedLearner.regularizedRisk(RdR1Distribution distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
double	EmpiricalLearningMetricEstimator.structuralRisk(RdR1Distribution distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)	Compute the Structural Sample Risk
double	GeneralizedLearner.structuralRisk(RdR1Distribution distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
EmpiricalPenaltySupremum	EmpiricalLearningMetricEstimator.supremumEmpiricalRisk(RdR1Distribution distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)	Compute the Supremum Empirical Sample Risk
EmpiricalPenaltySupremum	GeneralizedLearner.supremumEmpiricalRisk(RdR1Distribution distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
EmpiricalPenaltySupremum	EmpiricalLearningMetricEstimator.supremumRegularizedRisk(RdR1Distribution distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)	Compute the Supremum Regularized Sample Risk
EmpiricalPenaltySupremum	GeneralizedLearner.supremumRegularizedRisk(RdR1Distribution distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
EmpiricalPenaltySupremum	EmpiricalLearningMetricEstimator.supremumStructuralRisk(RdR1Distribution distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)	Compute the Supremum Structural Sample Risk
EmpiricalPenaltySupremum	GeneralizedLearner.supremumStructuralRisk(RdR1Distribution distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)

Constructors in org.drip.learning.rxtor1 with parameters of type RdR1Distribution

Constructor	Description
EmpiricalPenaltySupremumEstimator(int iSupremumPenaltyLossMode, EmpiricalLearningMetricEstimator elme, GeneralizedValidatedVector gvviY, R1R1Distribution distR1R1, RdR1Distribution distRdR1)	EmpiricalPenaltySupremumEstimator Constructor