DescribePredictorResponse class
Constructors
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DescribePredictorResponse({String? algorithmArn, List<String>? autoMLAlgorithmArns, DateTime? creationTime, List<String>? datasetImportJobArns, EncryptionConfig? encryptionConfig, EvaluationParameters? evaluationParameters, FeaturizationConfig? featurizationConfig, int? forecastHorizon, List<String>? forecastTypes, HyperParameterTuningJobConfig? hPOConfig, InputDataConfig? inputDataConfig, DateTime? lastModificationTime, String? message, bool? performAutoML, bool? performHPO, String? predictorArn, PredictorExecutionDetails? predictorExecutionDetails, String? predictorName, String? status, Map<String, String>? trainingParameters})
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DescribePredictorResponse.fromJson(Map<String, dynamic> json)
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factory
Properties
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algorithmArn
→ String?
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The Amazon Resource Name (ARN) of the algorithm used for model training.
final
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autoMLAlgorithmArns
→ List<String>?
-
When
PerformAutoML is specified, the ARN of the chosen
algorithm.
final
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creationTime
→ DateTime?
-
When the model training task was created.
final
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datasetImportJobArns
→ List<String>?
-
An array of the ARNs of the dataset import jobs used to import training data
for the predictor.
final
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encryptionConfig
→ EncryptionConfig?
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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.
final
-
evaluationParameters
→ EvaluationParameters?
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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.
final
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featurizationConfig
→ FeaturizationConfig?
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The featurization configuration.
final
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forecastHorizon
→ int?
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The number of time-steps of the forecast. The forecast horizon is also
called the prediction length.
final
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forecastTypes
→ List<String>?
-
The forecast types used during predictor training. Default value is
"0.1","0.5","0.9"final
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hashCode
→ int
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The hash code for this object.
no setterinherited
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hPOConfig
→ HyperParameterTuningJobConfig?
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The hyperparameter override values for the algorithm.
final
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inputDataConfig
→ InputDataConfig?
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Describes the dataset group that contains the data to use to train the
predictor.
final
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lastModificationTime
→ DateTime?
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Initially, the same as
CreationTime (when the status is
CREATE_PENDING). This value is updated when training starts
(when the status changes to CREATE_IN_PROGRESS), and when
training has completed (when the status changes to ACTIVE) or
fails (when the status changes to CREATE_FAILED).
final
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message
→ String?
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If an error occurred, an informational message about the error.
final
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performAutoML
→ bool?
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Whether the predictor is set to perform AutoML.
final
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performHPO
→ bool?
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Whether the predictor is set to perform hyperparameter optimization (HPO).
final
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predictorArn
→ String?
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The ARN of the predictor.
final
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predictorExecutionDetails
→ 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.
final
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predictorName
→ String?
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The name of the predictor.
final
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runtimeType
→ Type
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A representation of the runtime type of the object.
no setterinherited
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status
→ String?
-
The status of the predictor. States include:
final
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trainingParameters
→ Map<String, String>?
-
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.
final
Methods
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noSuchMethod(Invocation invocation)
→ dynamic
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Invoked when a nonexistent method or property is accessed.
inherited
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toString()
→ String
-
A string representation of this object.
inherited
