IForecastingSettings Interface

Definition

[System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ForecastingSettingsTypeConverter))]
public interface IForecastingSettings : Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Runtime.IJsonSerializable
[<System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ForecastingSettingsTypeConverter))>]
type IForecastingSettings = interface
    interface IJsonSerializable
Public Interface IForecastingSettings
Implements IJsonSerializable
Derived
Attributes
Implements

Properties

CountryOrRegionForHoliday

Country or region for holidays for forecasting tasks. These should be ISO 3166 two-letter country/region codes, for example 'US' or 'GB'.

CvStepSize

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.

FeatureLag

Flag for generating lags for the numeric features with 'auto' or null.

ForecastHorizonMode

[Required] Set forecast horizon value selection mode.

Frequency

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.

SeasonalityMode

[Required] Seasonality mode.

ShortSeriesHandlingConfig

The parameter defining how if AutoML should handle short time series.

TargetAggregateFunction

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".

TargetLagMode

[Required] Set target lags mode - Auto/Custom

TargetRollingWindowSizeMode

[Required] TargetRollingWindowSiz detection mode.

TimeColumnName

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.

TimeSeriesIdColumnName

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.

UseStl

Configure STL Decomposition of the time-series target column.

Methods

ToJson(JsonObject, SerializationMode) (Inherited from IJsonSerializable)

Applies to