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ArmMachineLearningModelFactory.MachineLearningForecasting Method

Definition

Namespace:
Azure.ResourceManager.MachineLearning.Models
Assembly:
Azure.ResourceManager.MachineLearning.dll
Package:
Azure.ResourceManager.MachineLearning v1.3.0
Source:
ArmMachineLearningModelFactory.cs

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