ArmMachineLearningModelFactory.MachineLearningForecasting Method

Definition

Namespace:: Azure.ResourceManager.MachineLearning.Models

Assembly:: Azure.ResourceManager.MachineLearning.dll

Package:: Azure.ResourceManager.MachineLearning v1.3.0

Source:: ArmMachineLearningModelFactory.cs

Important

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Forecasting task in AutoML Table vertical.

public static Azure.ResourceManager.MachineLearning.Models.MachineLearningForecasting MachineLearningForecasting(Azure.ResourceManager.MachineLearning.Models.MachineLearningLogVerbosity? logVerbosity = default, string targetColumnName = default, Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput trainingData = default, System.Collections.Generic.IEnumerable<string> cvSplitColumnNames = default, Azure.ResourceManager.MachineLearning.Models.TableVerticalFeaturizationSettings featurizationSettings = default, Azure.ResourceManager.MachineLearning.Models.TableVerticalLimitSettings limitSettings = default, Azure.ResourceManager.MachineLearning.Models.NCrossValidations nCrossValidations = default, Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput testData = default, double? testDataSize = default, Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput validationData = default, double? validationDataSize = default, string weightColumnName = default, Azure.ResourceManager.MachineLearning.Models.ForecastingSettings forecastingSettings = default, Azure.ResourceManager.MachineLearning.Models.ForecastingPrimaryMetric? primaryMetric = default, Azure.ResourceManager.MachineLearning.Models.ForecastingTrainingSettings trainingSettings = default);

static member MachineLearningForecasting : Nullable<Azure.ResourceManager.MachineLearning.Models.MachineLearningLogVerbosity> * string * Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput * seq<string> * Azure.ResourceManager.MachineLearning.Models.TableVerticalFeaturizationSettings * Azure.ResourceManager.MachineLearning.Models.TableVerticalLimitSettings * Azure.ResourceManager.MachineLearning.Models.NCrossValidations * Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput * Nullable<double> * Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput * Nullable<double> * string * Azure.ResourceManager.MachineLearning.Models.ForecastingSettings * Nullable<Azure.ResourceManager.MachineLearning.Models.ForecastingPrimaryMetric> * Azure.ResourceManager.MachineLearning.Models.ForecastingTrainingSettings -> Azure.ResourceManager.MachineLearning.Models.MachineLearningForecasting

Public Shared Function MachineLearningForecasting (Optional logVerbosity As Nullable(Of MachineLearningLogVerbosity) = Nothing, Optional targetColumnName As String = Nothing, Optional trainingData As MachineLearningTableJobInput = Nothing, Optional cvSplitColumnNames As IEnumerable(Of String) = Nothing, Optional featurizationSettings As TableVerticalFeaturizationSettings = Nothing, Optional limitSettings As TableVerticalLimitSettings = Nothing, Optional nCrossValidations As NCrossValidations = Nothing, Optional testData As MachineLearningTableJobInput = Nothing, Optional testDataSize As Nullable(Of Double) = Nothing, Optional validationData As MachineLearningTableJobInput = Nothing, Optional validationDataSize As Nullable(Of Double) = Nothing, Optional weightColumnName As String = Nothing, Optional forecastingSettings As ForecastingSettings = Nothing, Optional primaryMetric As Nullable(Of ForecastingPrimaryMetric) = Nothing, Optional trainingSettings As ForecastingTrainingSettings = Nothing) As MachineLearningForecasting

Parameters

logVerbosity: Nullable<MachineLearningLogVerbosity>

Enum for setting log verbosity.

targetColumnName: String

Target column name: This is prediction values column. Also known as label column name in context of classification tasks.

trainingData: MachineLearningTableJobInput

[Required] Training data input.

cvSplitColumnNames: IEnumerable<String>

Columns to use for CVSplit data.

featurizationSettings: TableVerticalFeaturizationSettings

Featurization inputs needed for AutoML job.

limitSettings: TableVerticalLimitSettings

Execution constraints for AutoMLJob.

nCrossValidations: NCrossValidations

Number of cross validation folds to be applied on training dataset when validation dataset is not provided.

testData: MachineLearningTableJobInput

Test data input.

testDataSize: Nullable<Double>

The fraction of test dataset that needs to be set aside for validation purpose. Values between (0.0 , 1.0) Applied when validation dataset is not provided.

validationData: MachineLearningTableJobInput

Validation data inputs.

validationDataSize: Nullable<Double>

The fraction of training dataset that needs to be set aside for validation purpose. Values between (0.0 , 1.0) Applied when validation dataset is not provided.

weightColumnName: String

The name of the sample weight column. Automated ML supports a weighted column as an input, causing rows in the data to be weighted up or down.

forecastingSettings: ForecastingSettings

Forecasting task specific inputs.

primaryMetric: Nullable<ForecastingPrimaryMetric>

Primary metrics for Forecasting task.

trainingSettings: ForecastingTrainingSettings

Inputs for training phase for an AutoML Job.

Returns

MachineLearningForecasting

A new MachineLearningForecasting instance for mocking.

Applies to

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