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HingeLoss Class

  • Reference

Definition

Namespace:
Microsoft.ML.Trainers
Assembly:
Microsoft.ML.Data.dll
Package:
Microsoft.ML v4.0.1
Package:
Microsoft.ML v1.0.0
Package:
Microsoft.ML v1.1.0
Package:
Microsoft.ML v1.2.0
Package:
Microsoft.ML v1.3.1
Package:
Microsoft.ML v1.4.0
Package:
Microsoft.ML v1.5.5
Package:
Microsoft.ML v1.6.0
Package:
Microsoft.ML v1.7.0
Package:
Microsoft.ML v2.0.1
Package:
Microsoft.ML v3.0.1
Package:
Microsoft.ML v5.0.0-preview.1.25125.4
Source:
LossFunctions.cs
Source:
LossFunctions.cs
Source:
LossFunctions.cs

Hinge Loss, commonly used in classification tasks.

public sealed class HingeLoss : Microsoft.ML.Trainers.ILossFunction<float,float>, Microsoft.ML.Trainers.ISupportSdcaClassificationLoss
type HingeLoss = class
    interface ISupportSdcaClassificationLoss
    interface ISupportSdcaLoss
    interface IScalarLoss
    interface ILossFunction<single, single>
    interface IClassificationLoss
Public NotInheritable Class HingeLoss
Implements ILossFunction(Of Single, Single), ISupportSdcaClassificationLoss
Inheritance
Object
HingeLoss
Implements
IClassificationLoss ILossFunction<Single,Single> IScalarLoss ISupportSdcaClassificationLoss ISupportSdcaLoss

Remarks

The Hinge Loss function is defined as:

$L(\hat{y}, y) = max(0, m - y\hat{y})$

where $\hat{y}$ is the predicted score, $y \in \{-1, 1\}$ is the true label, and $m$ is the margin parameter set to 1 by default.

Note that the labels used in this calculation are -1 and 1, unlike Log Loss, where the labels used are 0 and 1. Also unlike Log Loss, $\hat{y}$ is the raw predicted score, not the predicted probability (which is calculated by applying a sigmoid function to the predicted score).

While the hinge loss function is both convex and continuous, it is not smooth (that is not differentiable) at $y\hat{y} = m$. Consequently, it cannot be used with gradient descent methods or stochastic gradient descent methods, which rely on differentiability over the entire ___domain.

For more, see Hinge Loss for classification.

Applies to