PoissonLoss 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 v4.0.0-preview.24522.7

Source:: LossFunctions.cs

Source:: LossFunctions.cs

Source:: LossFunctions.cs

Important

Some information relates to prerelease product that may be substantially modified before it’s released. Microsoft makes no warranties, express or implied, with respect to the information provided here.

Poisson Loss function for Poisson Regression.

public sealed class PoissonLoss : Microsoft.ML.Trainers.ILossFunction<float,float>, Microsoft.ML.Trainers.IRegressionLoss

type PoissonLoss = class
    interface IRegressionLoss
    interface IScalarLoss
    interface ILossFunction<single, single>

Public NotInheritable Class PoissonLoss
Implements ILossFunction(Of Single, Single), IRegressionLoss

Inheritance: Object
PoissonLoss

Implements: ILossFunction<Single,Single> IRegressionLoss IScalarLoss

Remarks

The Poisson Loss function is defined as:

$L (\hat{y}, y) = e^{\hat{y}} - y \hat{y}$

where $\hat{y}$ is the predicted value, $y$ is the true label.

Constructors

PoissonLoss()

Methods

Derivative(Single, Single)
Loss(Single, Single)

Applies to

Product	Versions
ML.NET	1.0.0, 1.1.0, 1.2.0, 1.3.1, 1.4.0, 1.5.0, 1.6.0, 1.7.0, 2.0.0, 3.0.0, Preview, 4.0.0

Share via