ISupportSdcaRegressionLoss Interface

Definition

Namespace:

Microsoft.ML.Trainers

Assembly:

Microsoft.ML.Data.dll

Package:

Microsoft.ML v3.0.1

public interface ISupportSdcaRegressionLoss : Microsoft.ML.Trainers.ILossFunction<float,float>, Microsoft.ML.Trainers.IRegressionLoss, Microsoft.ML.Trainers.ISupportSdcaLoss

type ISupportSdcaRegressionLoss = interface
    interface ISupportSdcaLoss
    interface IScalarLoss
    interface ILossFunction<single, single>
    interface IRegressionLoss

Public Interface ISupportSdcaRegressionLoss
Implements ILossFunction(Of Single, Single), IRegressionLoss, ISupportSdcaLoss

Derived

Microsoft.ML.Trainers.SquaredLoss

Implements

ILossFunction<Single,Single> IRegressionLoss IScalarLoss ISupportSdcaLoss

Methods

ComputeDualUpdateInvariant(Single)	(Inherited from ISupportSdcaLoss)
Derivative(Single, Single)	Derivative of the loss function with respect to output (Inherited from IScalarLoss)
DualLoss(Single, Single)	The dual loss function for a training example. If f(x) denotes the loss function on an individual training example, then this function returns -f*(-x*), where f*(x*) is the Fenchel conjugate of f(x). (Inherited from ISupportSdcaLoss)
DualUpdate(Single, Single, Single, Single, Int32)	Compute the dual update (\Delta\alpha_i) in SDCA alpha: dual variable at the specified instance lambdaN: L2 const x number of instances cached invariant, hinted by the method above (Inherited from ISupportSdcaLoss)
Loss(TOutput, TLabel)	Computes the loss given the output and the ground truth. Note that the return value has type Double because the loss is usually accumulated over many instances. (Inherited from ILossFunction<TOutput,TLabel>)