Package software.amazon.awssdk.services.forecast.model

Class DescribePredictorResponse

    • Method Detail

      • predictorArn

        public final String predictorArn()

        The ARN of the predictor.

        Returns:
        The ARN of the predictor.

      • predictorName

        public final String predictorName()

        The name of the predictor.

        Returns:
        The name of the predictor.

      • algorithmArn

        public final String algorithmArn()

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

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

      • hasAutoMLAlgorithmArns

        public final boolean hasAutoMLAlgorithmArns()
        For responses, this returns true if the service returned a value for the AutoMLAlgorithmArns property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

      • autoMLAlgorithmArns

        public final List<String> autoMLAlgorithmArns()

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

        Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

        This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasAutoMLAlgorithmArns() method.

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

      • forecastHorizon

        public final Integer forecastHorizon()

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

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

      • hasForecastTypes

        public final boolean hasForecastTypes()
        For responses, this returns true if the service returned a value for the ForecastTypes property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

      • forecastTypes

        public final List<String> forecastTypes()

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

        Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

        This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasForecastTypes() method.

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

      • performAutoML

        public final Boolean performAutoML()

        Whether the predictor is set to perform AutoML.

        Returns:
        Whether the predictor is set to perform AutoML.

      • autoMLOverrideStrategy

        public final 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.

        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.

        If the service returns an enum value that is not available in the current SDK version, autoMLOverrideStrategy will return AutoMLOverrideStrategy.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from autoMLOverrideStrategyAsString().

        Returns:

        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.

        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.

        See Also:
        AutoMLOverrideStrategy

      • autoMLOverrideStrategyAsString

        public final String autoMLOverrideStrategyAsString()

        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.

        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.

        If the service returns an enum value that is not available in the current SDK version, autoMLOverrideStrategy will return AutoMLOverrideStrategy.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from autoMLOverrideStrategyAsString().

        Returns:

        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.

        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.

        See Also:
        AutoMLOverrideStrategy

      • performHPO

        public final Boolean performHPO()

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

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

      • hasTrainingParameters

        public final boolean hasTrainingParameters()
        For responses, this returns true if the service returned a value for the TrainingParameters property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

      • trainingParameters

        public final Map<String,​String> 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.

        Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

        This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasTrainingParameters() method.

        Returns:
        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.

      • evaluationParameters

        public final 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.

        Returns:
        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.

      • hpoConfig

        public final HyperParameterTuningJobConfig hpoConfig()

        The hyperparameter override values for the algorithm.

        Returns:
        The hyperparameter override values for the algorithm.

      • inputDataConfig

        public final InputDataConfig inputDataConfig()

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

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

      • featurizationConfig

        public final FeaturizationConfig featurizationConfig()

        The featurization configuration.

        Returns:
        The featurization configuration.

      • encryptionConfig

        public final 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.

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

      • predictorExecutionDetails

        public final 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.

        Returns:
        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.

      • estimatedTimeRemainingInMinutes

        public final Long estimatedTimeRemainingInMinutes()

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

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

      • hasDatasetImportJobArns

        public final boolean hasDatasetImportJobArns()
        For responses, this returns true if the service returned a value for the DatasetImportJobArns property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

      • datasetImportJobArns

        public final List<String> datasetImportJobArns()

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

        Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

        This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasDatasetImportJobArns() method.

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

      • status

        public final String status()

        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.

        Returns:
        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.

      • message

        public final String message()

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

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

      • creationTime

        public final Instant creationTime()

        When the model training task was created.

        Returns:
        When the model training task was created.

      • lastModificationTime

        public final Instant lastModificationTime()

        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.

        Returns:
        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.

      • toString

        public final String toString()
        Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
        Overrides:
        toString in class Object