LinearMulticlassModelParametersBase Class

Reference

Definition

Namespace:: Microsoft.ML.Trainers

Assembly:: Microsoft.ML.StandardTrainers.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:: MulticlassLogisticRegression.cs

Source:: MulticlassLogisticRegression.cs

Source:: MulticlassLogisticRegression.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.

Common linear model of multiclass classifiers. LinearMulticlassModelParameters contains a single linear model per class.

public abstract class LinearMulticlassModelParametersBase : Microsoft.ML.Trainers.ModelParametersBase<Microsoft.ML.Data.VBuffer<float>>

type LinearMulticlassModelParametersBase = class
    inherit ModelParametersBase<VBuffer<single>>

Public MustInherit Class LinearMulticlassModelParametersBase
Inherits ModelParametersBase(Of VBuffer(Of Single))

Inheritance: Object

ModelParametersBase<VBuffer<Single>>
LinearMulticlassModelParametersBase

Derived: Microsoft.ML.Trainers.LinearMulticlassModelParameters

Microsoft.ML.Trainers.MaximumEntropyModelParameters

Fields

Statistics

Methods

GetBiases()	Gets the biases for the logistic regression predictor.
GetWeights(VBuffer<Single>[], Int32)	Copies the weight vector for each class into a set of buffers.

Explicit Interface Implementations

ICanSaveModel.Save(ModelSaveContext)

(Inherited from ModelParametersBase<TOutput>)

Applies to

Produkto	Mga Bersyon
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, 4.0.0, Preview

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