The London Perl and Raku Workshop takes place on 26th Oct 2024. If your company depends on Perl, please consider sponsoring and/or attending.
 / 
Paws-0.46
River stage two • 9 direct dependents • 11 total dependents
/ Paws::Forecast::DescribePredictorResponse

NAME

Paws::Forecast::DescribePredictorResponse

ATTRIBUTES

AlgorithmArn => Str

The Amazon Resource Name (ARN) of the algorithm used for model training.

AutoMLAlgorithmArns => ArrayRef[Str|Undef]

When PerformAutoML is specified, the ARN of the chosen algorithm.

AutoMLOverrideStrategy => Str

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

Valid values are: "LatencyOptimized" =head2 CreationTime => Str

When the model training task was created.

DatasetImportJobArns => ArrayRef[Str|Undef]

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

EncryptionConfig => Paws::Forecast::EncryptionConfig

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

EstimatedTimeRemainingInMinutes => Int

The estimated time remaining in minutes for the predictor training job to complete.

EvaluationParameters => Paws::Forecast::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 => Paws::Forecast::FeaturizationConfig

The featurization configuration.

ForecastHorizon => Int

The number of time-steps of the forecast. The forecast horizon is also called the prediction length.

ForecastTypes => ArrayRef[Str|Undef]

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

HPOConfig => Paws::Forecast::HyperParameterTuningJobConfig

The hyperparameter override values for the algorithm.

InputDataConfig => Paws::Forecast::InputDataConfig

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

LastModificationTime => Str

The last time the resource was modified. The timestamp depends on the status of the job:

  • CREATE_PENDING - The CreationTime.

  • CREATE_IN_PROGRESS - The current timestamp.

  • CREATE_STOPPING - The current timestamp.

  • CREATE_STOPPED - When the job stopped.

  • ACTIVE or CREATE_FAILED - When the job finished or failed.

Message => Str

If an error occurred, an informational message about the error.

PerformAutoML => Bool

Whether the predictor is set to perform AutoML.

PerformHPO => Bool

Whether the predictor is set to perform hyperparameter optimization (HPO).

PredictorArn => Str

The ARN of the predictor.

PredictorExecutionDetails => Paws::Forecast::PredictorExecutionDetails

Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor. You specify the number of backtests to perform when you call the operation.

PredictorName => Str

The name of the predictor.

Status => Str

The status of the predictor. States include:

  • ACTIVE

  • CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED

  • DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

  • CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

TrainingParameters => Paws::Forecast::TrainingParameters

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

_request_id => Str