ForecastingSettings interface

Package:

@azure/arm-machinelearning

Forecasting specific parameters.

Properties

countryOrRegionForHolidays	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.
featureLags	Flag for generating lags for the numeric features with 'auto' or null.
forecastHorizon	The desired maximum forecast horizon in units of time-series frequency.
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.
seasonality	Set time series seasonality as an integer multiple of the series frequency. If seasonality is set to 'auto', it will be inferred.
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".
targetLags	The number of past periods to lag from the target column.
targetRollingWindowSize	The number of past periods used to create a rolling window average of the target column.
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.
timeSeriesIdColumnNames	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.

Property Details

countryOrRegionForHolidays

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

countryOrRegionForHolidays?: string

Property Value

string

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.

cvStepSize?: number

Property Value

number

featureLags

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

featureLags?: string

Property Value

string

forecastHorizon

The desired maximum forecast horizon in units of time-series frequency.

forecastHorizon?: ForecastHorizonUnion

Property Value

ForecastHorizonUnion

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.

frequency?: string

Property Value

string

seasonality

Set time series seasonality as an integer multiple of the series frequency. If seasonality is set to 'auto', it will be inferred.

seasonality?: SeasonalityUnion

Property Value

SeasonalityUnion

shortSeriesHandlingConfig

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

shortSeriesHandlingConfig?: string

Property Value

string

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".

targetAggregateFunction?: string

Property Value

string

targetLags

The number of past periods to lag from the target column.

targetLags?: TargetLagsUnion

Property Value

TargetLagsUnion

targetRollingWindowSize

The number of past periods used to create a rolling window average of the target column.

targetRollingWindowSize?: TargetRollingWindowSizeUnion

Property Value

TargetRollingWindowSizeUnion

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.

timeColumnName?: string

Property Value

string

timeSeriesIdColumnNames

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.

timeSeriesIdColumnNames?: string[]

Property Value

string[]

useStl

Configure STL Decomposition of the time-series target column.

useStl?: string

Property Value

string