IForecasting Interface

Definition

Namespace:

Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401

Assembly:

Az.MachineLearningServices.private.dll

[System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ForecastingTypeConverter))]
public interface IForecasting : Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IAutoMlVertical, Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ITableVertical

[<System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ForecastingTypeConverter))>]
type IForecasting = interface
    interface IJsonSerializable
    interface ITableVertical
    interface IAutoMlVertical

Public Interface IForecasting
Implements IAutoMlVertical, ITableVertical

Derived

Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.Forecasting

Attributes

TypeConverterAttribute

Implements

IAutoMlVertical ITableVertical IJsonSerializable

Properties

CvSplitColumnName	Columns to use for CVSplit data. (Inherited from ITableVertical)
FeaturizationSettingBlockedTransformer	These transformers shall not be used in featurization. (Inherited from ITableVertical)
FeaturizationSettingColumnNameAndType	Dictionary of column name and its type (int, float, string, datetime etc). (Inherited from ITableVertical)
FeaturizationSettingDatasetLanguage	Dataset language, useful for the text data. (Inherited from ITableVertical)
FeaturizationSettingEnableDnnFeaturization	Determines whether to use Dnn based featurizers for data featurization. (Inherited from ITableVertical)
FeaturizationSettingMode	Featurization mode - User can keep the default 'Auto' mode and AutoML will take care of necessary transformation of the data in featurization phase. If 'Off' is selected then no featurization is done. If 'Custom' is selected then user can specify additional inputs to customize how featurization is done. (Inherited from ITableVertical)
FeaturizationSettingTransformerParam	User can specify additional transformers to be used along with the columns to which it would be applied and parameters for the transformer constructor. (Inherited from ITableVertical)
ForecastHorizonMode	[Required] Set forecast horizon value selection mode.
LimitSettingEnableEarlyTermination	Enable early termination, determines whether or not if AutoMLJob will terminate early if there is no score improvement in last 20 iterations. (Inherited from ITableVertical)
LimitSettingExitScore	Exit score for the AutoML job. (Inherited from ITableVertical)
LimitSettingMaxConcurrentTrial	Maximum Concurrent iterations. (Inherited from ITableVertical)
LimitSettingMaxCoresPerTrial	Max cores per iteration. (Inherited from ITableVertical)
LimitSettingMaxTrial	Number of iterations. (Inherited from ITableVertical)
LimitSettingTimeout	AutoML job timeout. (Inherited from ITableVertical)
LimitSettingTrialTimeout	Iteration timeout. (Inherited from ITableVertical)
LogVerbosity	Log verbosity for the job. (Inherited from IAutoMlVertical)
NCrossValidationMode	[Required] Mode for determining N-Cross validations. (Inherited from ITableVertical)
PrimaryMetric	Primary metric for forecasting task.
SeasonalityMode	[Required] Seasonality mode.
SettingCountryOrRegionForHoliday	Country or region for holidays for forecasting tasks. These should be ISO 3166 two-letter country/region codes, for example 'US' or 'GB'.
SettingCvStepSize	Number of periods between the origin time of one CV fold and the next fold. For example, if CVStepSize = 3 for daily data, the origin time for each fold will be three days apart.
SettingFeatureLag	Flag for generating lags for the numeric features with 'auto' or null.
SettingFrequency	When forecasting, this parameter represents the period with which the forecast is desired, for example daily, weekly, yearly, etc. The forecast frequency is dataset frequency by default.
SettingShortSeriesHandlingConfig	The parameter defining how if AutoML should handle short time series.
SettingTargetAggregateFunction	The function to be used to aggregate the time series target column to conform to a user specified frequency. If the TargetAggregateFunction is set i.e. not 'None', but the freq parameter is not set, the error is raised. The possible target aggregation functions are: "sum", "max", "min" and "mean".
SettingTimeColumnName	The name of the time column. This parameter is required when forecasting to specify the datetime column in the input data used for building the time series and inferring its frequency.
SettingTimeSeriesIdColumnName	The names of columns used to group a timeseries. It can be used to create multiple series. If grain is not defined, the data set is assumed to be one time-series. This parameter is used with task type forecasting.
SettingUseStl	Configure STL Decomposition of the time-series target column.
TargetColumnName	Target column name: This is prediction values column. Also known as label column name in context of classification tasks. (Inherited from IAutoMlVertical)
TargetLagMode	[Required] Set target lags mode - Auto/Custom
TargetRollingWindowSizeMode	[Required] TargetRollingWindowSiz detection mode.
TaskType	[Required] Task type for AutoMLJob. (Inherited from IAutoMlVertical)
TestDataDescription	Description for the input. (Inherited from ITableVertical)
TestDataJobInputType	[Required] Specifies the type of job. (Inherited from ITableVertical)
TestDataMode	Input Asset Delivery Mode. (Inherited from ITableVertical)
TestDataSize	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. (Inherited from ITableVertical)
TestDataUri	[Required] Input Asset URI. (Inherited from ITableVertical)
TrainingDataDescription	Description for the input. (Inherited from IAutoMlVertical)
TrainingDataJobInputType	[Required] Specifies the type of job. (Inherited from IAutoMlVertical)
TrainingDataMode	Input Asset Delivery Mode. (Inherited from IAutoMlVertical)
TrainingDataUri	[Required] Input Asset URI. (Inherited from IAutoMlVertical)
TrainingSettingAllowedTrainingAlgorithm	Allowed models for forecasting task.
TrainingSettingBlockedTrainingAlgorithm	Blocked models for forecasting task.
TrainingSettingEnableDnnTraining	Enable recommendation of DNN models.
TrainingSettingEnableModelExplainability	Flag to turn on explainability on best model.
TrainingSettingEnableOnnxCompatibleModel	Flag for enabling onnx compatible models.
TrainingSettingEnableStackEnsemble	Enable stack ensemble run.
TrainingSettingEnableVoteEnsemble	Enable voting ensemble run.
TrainingSettingEnsembleModelDownloadTimeout	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.
TrainingSettingStackEnsembleSettingStackMetaLearnerKWarg	Optional parameters to pass to the initializer of the meta-learner.
TrainingSettingStackEnsembleSettingStackMetaLearnerTrainPercentage	Specifies the proportion of the training set (when choosing train and validation type of training) to be reserved for training the meta-learner. Default value is 0.2.
TrainingSettingStackEnsembleSettingStackMetaLearnerType	The meta-learner is a model trained on the output of the individual heterogeneous models.
ValidationDataDescription	Description for the input. (Inherited from ITableVertical)
ValidationDataJobInputType	[Required] Specifies the type of job. (Inherited from ITableVertical)
ValidationDataMode	Input Asset Delivery Mode. (Inherited from ITableVertical)
ValidationDataSize	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. (Inherited from ITableVertical)
ValidationDataUri	[Required] Input Asset URI. (Inherited from ITableVertical)
WeightColumnName	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. (Inherited from ITableVertical)

Methods

ToJson(JsonObject, SerializationMode)

(Inherited from IJsonSerializable)