forecast/aws.sdk.kotlin.services.forecast.model/CreatePredictorRequest/Builder

Builder

Properties

The Amazon Resource Name (ARN) of the algorithm to use for model training. Required if PerformAutoML is not set to true.

autoMlOverrideStrategy

var autoMlOverrideStrategy: AutoMlOverrideStrategy?

The LatencyOptimized AutoML override strategy is only available in private beta. Contact Amazon Web Services Support or your account manager to learn more about access privileges.

encryptionConfig

var encryptionConfig: EncryptionConfig?

An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

evaluationParameters

var evaluationParameters: EvaluationParameters?

Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.

featurizationConfig

var featurizationConfig: FeaturizationConfig?

The featurization configuration.

forecastHorizon

var forecastHorizon: Int?

Specifies the number of time-steps that the model is trained to predict. The forecast horizon is also called the prediction length.

forecastTypes

var forecastTypes: List<String>?

Specifies 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.

hpoConfig

var hpoConfig: HyperParameterTuningJobConfig?

Provides hyperparameter override values for the algorithm. If you don't provide this parameter, Amazon Forecast uses default values. The individual algorithms specify which hyperparameters support hyperparameter optimization (HPO). For more information, see aws-forecast-choosing-recipes.

inputDataConfig

var inputDataConfig: InputDataConfig?

Describes the dataset group that contains the data to use to train the predictor.

optimizationMetric

var optimizationMetric: OptimizationMetric?

The accuracy metric used to optimize the predictor.

performAutoMl

var performAutoMl: Boolean?

Whether to perform AutoML. When Amazon Forecast performs AutoML, it evaluates the algorithms it provides and chooses the best algorithm and configuration for your training dataset.

performHpo

var performHpo: Boolean?

Whether to perform hyperparameter optimization (HPO). HPO finds optimal hyperparameter values for your training data. The process of performing HPO is known as running a hyperparameter tuning job.

predictorName

var predictorName: String?

A name for the predictor.