FieldAwareFactorizationMachineModelParameters Class

Definition

Namespace:

Microsoft.ML.Trainers

Assembly:

Microsoft.ML.StandardTrainers.dll

Package:

Microsoft.ML v3.0.1

Model parameters for FieldAwareFactorizationMachineTrainer.

public sealed class FieldAwareFactorizationMachineModelParameters : Microsoft.ML.Trainers.ModelParametersBase<float>

type FieldAwareFactorizationMachineModelParameters = class
    inherit ModelParametersBase<single>

Public NotInheritable Class FieldAwareFactorizationMachineModelParameters
Inherits ModelParametersBase(Of Single)

Inheritance

Object

ModelParametersBase<Single>

FieldAwareFactorizationMachineModelParameters

Properties

FeatureCount	Get the number of features. It's the symbol n in the doc: https://github.com/wschin/fast-ffm/blob/master/fast-ffm.pdf
FieldCount	Get the number of fields. It's the symbol m in the doc: https://github.com/wschin/fast-ffm/blob/master/fast-ffm.pdf
LatentDimension	Get the latent dimension. It's the length of v_{j, f} in the doc: https://github.com/wschin/fast-ffm/blob/master/fast-ffm.pdf

Methods

GetLatentWeights()

Latent representation of each feature. Note that one feature may have FieldCount latent vectors and each latent vector contains LatentDimension values. In the f-th field, the j-th feature's latent vector, v_{j, f} in the doc https://github.com/wschin/fast-ffm/blob/master/fast-ffm.pdf, starts at latentWeights[j * fieldCount * latentDim + f * latentDim]. The k-th element in v_{j, f} is latentWeights[j * fieldCount * latentDim + f * latentDim + k]. The size of the returned value is featureCount x fieldCount x latentDim.

GetLinearWeights()

The linear coefficients of the features. It's the symbol w in the doc: https://github.com/wschin/fast-ffm/blob/master/fast-ffm.pdf

Explicit Interface Implementations

ICanSaveModel.Save(ModelSaveContext)

(Inherited from ModelParametersBase<TOutput>)