ForecastingTrainingSettings Class

Definition

Namespace:

Azure.ResourceManager.MachineLearning.Models

Assembly:

Azure.ResourceManager.MachineLearning.dll

Package:

Azure.ResourceManager.MachineLearning v1.1.1

Source:

ForecastingTrainingSettings.cs

Forecasting Training related configuration.

public class ForecastingTrainingSettings : Azure.ResourceManager.MachineLearning.Models.MachineLearningTrainingSettings

type ForecastingTrainingSettings = class
    inherit MachineLearningTrainingSettings

Public Class ForecastingTrainingSettings
Inherits MachineLearningTrainingSettings

Inheritance

Object

MachineLearningTrainingSettings

ForecastingTrainingSettings

Constructors

ForecastingTrainingSettings()

Initializes a new instance of ForecastingTrainingSettings.

Properties

AllowedTrainingAlgorithms	Allowed models for forecasting task.
BlockedTrainingAlgorithms	Blocked models for forecasting task.
EnsembleModelDownloadTimeout	During VotingEnsemble and StackEnsemble model generation, multiple fitted models from the previous child runs are downloaded. Configure this parameter with a higher value than 300 secs, if more time is needed. (Inherited from MachineLearningTrainingSettings)
IsDnnTrainingEnabled	Enable recommendation of DNN models. (Inherited from MachineLearningTrainingSettings)
IsModelExplainabilityEnabled	Flag to turn on explainability on best model. (Inherited from MachineLearningTrainingSettings)
IsOnnxCompatibleModelsEnabled	Flag for enabling onnx compatible models. (Inherited from MachineLearningTrainingSettings)
IsStackEnsembleEnabled	Enable stack ensemble run. (Inherited from MachineLearningTrainingSettings)
IsVoteEnsembleEnabled	Enable voting ensemble run. (Inherited from MachineLearningTrainingSettings)
StackEnsembleSettings	Stack ensemble settings for stack ensemble run. (Inherited from MachineLearningTrainingSettings)
TrainingMode	TrainingMode mode - Setting to 'auto' is same as setting it to 'non-distributed' for now, however in the future may result in mixed mode or heuristics based mode selection. Default is 'auto'. If 'Distributed' then only distributed featurization is used and distributed algorithms are chosen. If 'NonDistributed' then only non distributed algorithms are chosen. (Inherited from MachineLearningTrainingSettings)