Builder
Properties
The data configuration for your dataset group and any additional datasets.
An Key Management Service (KMS) key and an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key. You can specify this optional object in the CreateDataset and CreatePredictor requests.
Create an Explainability resource for the predictor.
An array of dimension (field) names that specify how to group the generated forecast.
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 forecast types used to train a predictor. You can specify up to five forecast types. Forecast types can be quantiles from 0.01 to 0.99, by increments of 0.01 or higher. You can also specify the mean forecast with mean.
The configuration details for predictor monitoring. Provide a name for the monitor resource to enable predictor monitoring.
The accuracy metric used to optimize the predictor.
A unique name for the predictor
The ARN of the predictor to retrain or upgrade. This parameter is only used when retraining or upgrading a predictor. When creating a new predictor, do not specify a value for this parameter.
The time boundary Forecast uses to align and aggregate any data that doesn't align with your forecast frequency. Provide the unit of time and the time boundary as a key value pair. For more information on specifying a time boundary, see Specifying a Time Boundary. If you don't provide a time boundary, Forecast uses a set of Default Time Boundaries.
Functions
construct an aws.sdk.kotlin.services.forecast.model.DataConfig inside the given block
construct an aws.sdk.kotlin.services.forecast.model.EncryptionConfig inside the given block
construct an aws.sdk.kotlin.services.forecast.model.MonitorConfig inside the given block
construct an aws.sdk.kotlin.services.forecast.model.TimeAlignmentBoundary inside the given block