All Known Implementing Classes:: RegularizerRdCombinatorialToR1Continuous, RegularizerRdContinuousToR1Continuous

public interface RegularizerRdToR1

RegularizerRdToR1 exposes the Structural Loss and Risk for the specified Normed R^d To Normed R¹ Learning Function.

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Module = Computational Core Module
Library = Statistical Learning
Project = Agnostic Learning Bounds under Empirical Loss Minimization Schemes
Package = Statistical Learning Empirical Loss Regularizer

Method Summary

Modifier and Type	Method	Description
`double`	`lambda()`	Retrieve the Regularization Constant Lambda
`double`	`structuralLoss(RdToR1 funcRdToR1, double[][] aadblX)`	Compute the Regularization Sample Structural Loss
`double`	`structuralRisk(RdR1 distRdR1, RdToR1 funcRdToR1, double[][] aadblX, double[] adblY)`	Compute the Regularization Sample Structural Loss

Interface RegularizerRdToR1