Interface CreatePredictorRequest.Builder

All Superinterfaces:
AwsRequest.Builder, Buildable, CopyableBuilder<CreatePredictorRequest.Builder,CreatePredictorRequest>, ForecastRequest.Builder, SdkBuilder<CreatePredictorRequest.Builder,CreatePredictorRequest>, SdkPojo, SdkRequest.Builder
Enclosing class:
CreatePredictorRequest

public static interface CreatePredictorRequest.Builder extends ForecastRequest.Builder, SdkPojo, CopyableBuilder<CreatePredictorRequest.Builder,CreatePredictorRequest>
  • Method Details

    • predictorName

      CreatePredictorRequest.Builder predictorName(String predictorName)

      A name for the predictor.

      Parameters:
      predictorName - A name for the predictor.
      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • algorithmArn

      CreatePredictorRequest.Builder algorithmArn(String algorithmArn)

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

      Supported algorithms:

      • arn:aws:forecast:::algorithm/ARIMA

      • arn:aws:forecast:::algorithm/CNN-QR

      • arn:aws:forecast:::algorithm/Deep_AR_Plus

      • arn:aws:forecast:::algorithm/ETS

      • arn:aws:forecast:::algorithm/NPTS

      • arn:aws:forecast:::algorithm/Prophet

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

      Supported algorithms:

      • arn:aws:forecast:::algorithm/ARIMA

      • arn:aws:forecast:::algorithm/CNN-QR

      • arn:aws:forecast:::algorithm/Deep_AR_Plus

      • arn:aws:forecast:::algorithm/ETS

      • arn:aws:forecast:::algorithm/NPTS

      • arn:aws:forecast:::algorithm/Prophet

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • forecastHorizon

      CreatePredictorRequest.Builder forecastHorizon(Integer forecastHorizon)

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

      For example, if you configure a dataset for daily data collection (using the DataFrequency parameter of the CreateDataset operation) and set the forecast horizon to 10, the model returns predictions for 10 days.

      The maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.

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

      For example, if you configure a dataset for daily data collection (using the DataFrequency parameter of the CreateDataset operation) and set the forecast horizon to 10, the model returns predictions for 10 days.

      The maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • forecastTypes

      CreatePredictorRequest.Builder forecastTypes(Collection<String> forecastTypes)

      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.

      The default value is ["0.10", "0.50", "0.9"].

      Parameters:
      forecastTypes - 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.

      The default value is ["0.10", "0.50", "0.9"].

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • forecastTypes

      CreatePredictorRequest.Builder forecastTypes(String... forecastTypes)

      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.

      The default value is ["0.10", "0.50", "0.9"].

      Parameters:
      forecastTypes - 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.

      The default value is ["0.10", "0.50", "0.9"].

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • performAutoML

      CreatePredictorRequest.Builder performAutoML(Boolean performAutoML)

      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.

      The default value is false. In this case, you are required to specify an algorithm.

      Set PerformAutoML to true to have Amazon Forecast perform AutoML. This is a good option if you aren't sure which algorithm is suitable for your training data. In this case, PerformHPO must be false.

      Parameters:
      performAutoML - 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.

      The default value is false. In this case, you are required to specify an algorithm.

      Set PerformAutoML to true to have Amazon Forecast perform AutoML. This is a good option if you aren't sure which algorithm is suitable for your training data. In this case, PerformHPO must be false.

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • autoMLOverrideStrategy

      CreatePredictorRequest.Builder autoMLOverrideStrategy(String 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.

      Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use LatencyOptimized.

      This parameter is only valid for predictors trained using AutoML.

      Parameters:
      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.

      Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use LatencyOptimized.

      This parameter is only valid for predictors trained using AutoML.

      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • autoMLOverrideStrategy

      CreatePredictorRequest.Builder autoMLOverrideStrategy(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.

      Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use LatencyOptimized.

      This parameter is only valid for predictors trained using AutoML.

      Parameters:
      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.

      Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use LatencyOptimized.

      This parameter is only valid for predictors trained using AutoML.

      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • performHPO

      CreatePredictorRequest.Builder performHPO(Boolean performHPO)

      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.

      The default value is false. In this case, Amazon Forecast uses default hyperparameter values from the chosen algorithm.

      To override the default values, set PerformHPO to true and, optionally, supply the HyperParameterTuningJobConfig object. The tuning job specifies a metric to optimize, which hyperparameters participate in tuning, and the valid range for each tunable hyperparameter. In this case, you are required to specify an algorithm and PerformAutoML must be false.

      The following algorithms support HPO:

      • DeepAR+

      • CNN-QR

      Parameters:
      performHPO - 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.

      The default value is false. In this case, Amazon Forecast uses default hyperparameter values from the chosen algorithm.

      To override the default values, set PerformHPO to true and, optionally, supply the HyperParameterTuningJobConfig object. The tuning job specifies a metric to optimize, which hyperparameters participate in tuning, and the valid range for each tunable hyperparameter. In this case, you are required to specify an algorithm and PerformAutoML must be false.

      The following algorithms support HPO:

      • DeepAR+

      • CNN-QR

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • trainingParameters

      CreatePredictorRequest.Builder trainingParameters(Map<String,String> trainingParameters)

      The hyperparameters to override for model training. The hyperparameters that you can override are listed in the individual algorithms. For the list of supported algorithms, see aws-forecast-choosing-recipes.

      Parameters:
      trainingParameters - The hyperparameters to override for model training. The hyperparameters that you can override are listed in the individual algorithms. For the list of supported algorithms, see aws-forecast-choosing-recipes.
      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • evaluationParameters

      CreatePredictorRequest.Builder evaluationParameters(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.

      Parameters:
      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:
      Returns a reference to this object so that method calls can be chained together.
    • evaluationParameters

      default CreatePredictorRequest.Builder evaluationParameters(Consumer<EvaluationParameters.Builder> 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.

      This is a convenience method that creates an instance of the EvaluationParameters.Builder avoiding the need to create one manually via EvaluationParameters.builder().

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to evaluationParameters(EvaluationParameters).

      Parameters:
      evaluationParameters - a consumer that will call methods on EvaluationParameters.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • hpoConfig

      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.

      If you included the HPOConfig object, you must set PerformHPO to true.

      Parameters:
      hpoConfig - 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.

      If you included the HPOConfig object, you must set PerformHPO to true.

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • hpoConfig

      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.

      If you included the HPOConfig object, you must set PerformHPO to true.

      This is a convenience method that creates an instance of the HyperParameterTuningJobConfig.Builder avoiding the need to create one manually via HyperParameterTuningJobConfig.builder().

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to hpoConfig(HyperParameterTuningJobConfig).

      Parameters:
      hpoConfig - a consumer that will call methods on HyperParameterTuningJobConfig.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • inputDataConfig

      CreatePredictorRequest.Builder inputDataConfig(InputDataConfig inputDataConfig)

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

      Parameters:
      inputDataConfig - Describes the dataset group that contains the data to use to train the predictor.
      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • inputDataConfig

      default CreatePredictorRequest.Builder inputDataConfig(Consumer<InputDataConfig.Builder> inputDataConfig)

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

      This is a convenience method that creates an instance of the InputDataConfig.Builder avoiding the need to create one manually via InputDataConfig.builder().

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to inputDataConfig(InputDataConfig).

      Parameters:
      inputDataConfig - a consumer that will call methods on InputDataConfig.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • featurizationConfig

      CreatePredictorRequest.Builder featurizationConfig(FeaturizationConfig featurizationConfig)

      The featurization configuration.

      Parameters:
      featurizationConfig - The featurization configuration.
      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • featurizationConfig

      default CreatePredictorRequest.Builder featurizationConfig(Consumer<FeaturizationConfig.Builder> featurizationConfig)

      The featurization configuration.

      This is a convenience method that creates an instance of the FeaturizationConfig.Builder avoiding the need to create one manually via FeaturizationConfig.builder().

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to featurizationConfig(FeaturizationConfig).

      Parameters:
      featurizationConfig - a consumer that will call methods on FeaturizationConfig.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • encryptionConfig

      CreatePredictorRequest.Builder encryptionConfig(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.

      Parameters:
      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:
      Returns a reference to this object so that method calls can be chained together.
    • encryptionConfig

      default CreatePredictorRequest.Builder encryptionConfig(Consumer<EncryptionConfig.Builder> encryptionConfig)

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

      This is a convenience method that creates an instance of the EncryptionConfig.Builder avoiding the need to create one manually via EncryptionConfig.builder().

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to encryptionConfig(EncryptionConfig).

      Parameters:
      encryptionConfig - a consumer that will call methods on EncryptionConfig.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • tags

      The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

      The following basic restrictions apply to tags:

      • Maximum number of tags per resource - 50.

      • For each resource, each tag key must be unique, and each tag key can have only one value.

      • Maximum key length - 128 Unicode characters in UTF-8.

      • Maximum value length - 256 Unicode characters in UTF-8.

      • If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

      • Tag keys and values are case sensitive.

      • Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

      Parameters:
      tags - The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

      The following basic restrictions apply to tags:

      • Maximum number of tags per resource - 50.

      • For each resource, each tag key must be unique, and each tag key can have only one value.

      • Maximum key length - 128 Unicode characters in UTF-8.

      • Maximum value length - 256 Unicode characters in UTF-8.

      • If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

      • Tag keys and values are case sensitive.

      • Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • tags

      The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

      The following basic restrictions apply to tags:

      • Maximum number of tags per resource - 50.

      • For each resource, each tag key must be unique, and each tag key can have only one value.

      • Maximum key length - 128 Unicode characters in UTF-8.

      • Maximum value length - 256 Unicode characters in UTF-8.

      • If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

      • Tag keys and values are case sensitive.

      • Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

      Parameters:
      tags - The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

      The following basic restrictions apply to tags:

      • Maximum number of tags per resource - 50.

      • For each resource, each tag key must be unique, and each tag key can have only one value.

      • Maximum key length - 128 Unicode characters in UTF-8.

      • Maximum value length - 256 Unicode characters in UTF-8.

      • If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

      • Tag keys and values are case sensitive.

      • Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • tags

      The optional metadata that you apply to the predictor to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

      The following basic restrictions apply to tags:

      • Maximum number of tags per resource - 50.

      • For each resource, each tag key must be unique, and each tag key can have only one value.

      • Maximum key length - 128 Unicode characters in UTF-8.

      • Maximum value length - 256 Unicode characters in UTF-8.

      • If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

      • Tag keys and values are case sensitive.

      • Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for Amazon Web Services use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

      This is a convenience method that creates an instance of the Tag.Builder avoiding the need to create one manually via Tag.builder().

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to tags(List<Tag>).

      Parameters:
      tags - a consumer that will call methods on Tag.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • optimizationMetric

      CreatePredictorRequest.Builder optimizationMetric(String optimizationMetric)

      The accuracy metric used to optimize the predictor.

      Parameters:
      optimizationMetric - The accuracy metric used to optimize the predictor.
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • optimizationMetric

      CreatePredictorRequest.Builder optimizationMetric(OptimizationMetric optimizationMetric)

      The accuracy metric used to optimize the predictor.

      Parameters:
      optimizationMetric - The accuracy metric used to optimize the predictor.
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:
    • overrideConfiguration

      CreatePredictorRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)
      Description copied from interface: AwsRequest.Builder
      Add an optional request override configuration.
      Specified by:
      overrideConfiguration in interface AwsRequest.Builder
      Parameters:
      overrideConfiguration - The override configuration.
      Returns:
      This object for method chaining.
    • overrideConfiguration

      Description copied from interface: AwsRequest.Builder
      Add an optional request override configuration.
      Specified by:
      overrideConfiguration in interface AwsRequest.Builder
      Parameters:
      builderConsumer - A Consumer to which an empty AwsRequestOverrideConfiguration.Builder will be given.
      Returns:
      This object for method chaining.