TimeSeriesForecastingJobConfig
The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
Types
Properties
Stores the configuration information for how model candidates are generated using an AutoML job V2.
How long a job is allowed to run, or how many candidates a job is allowed to generate.
A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig.
The frequency of predictions in a forecast.
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.
The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.
The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
The collection of components that defines the time-series.
The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.