Interface CreateAutoPredictorRequest.Builder

All Superinterfaces:
AwsRequest.Builder, Buildable, CopyableBuilder<CreateAutoPredictorRequest.Builder,CreateAutoPredictorRequest>, ForecastRequest.Builder, SdkBuilder<CreateAutoPredictorRequest.Builder,CreateAutoPredictorRequest>, SdkPojo, SdkRequest.Builder
Enclosing class:
CreateAutoPredictorRequest
public static interface CreateAutoPredictorRequest.Builder extends ForecastRequest.Builder, SdkPojo, CopyableBuilder<CreateAutoPredictorRequest.Builder,CreateAutoPredictorRequest>

  • Method Details

    • predictorName

      CreateAutoPredictorRequest.Builder predictorName(String predictorName)

      A unique name for the predictor

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

    • forecastHorizon

      CreateAutoPredictorRequest.Builder forecastHorizon(Integer forecastHorizon)

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

      The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the TARGET_TIME_SERIES dataset length. If you are retraining an existing AutoPredictor, then the maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.

      If you are upgrading to an AutoPredictor or retraining an existing AutoPredictor, you cannot update the forecast horizon parameter. You can meet this requirement by providing longer time-series in the dataset.

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

      The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the TARGET_TIME_SERIES dataset length. If you are retraining an existing AutoPredictor, then the maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.

      If you are upgrading to an AutoPredictor or retraining an existing AutoPredictor, you cannot update the forecast horizon parameter. You can meet this requirement by providing longer time-series in the dataset.

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

    • forecastTypes

      CreateAutoPredictorRequest.Builder forecastTypes(Collection<String> forecastTypes)

      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.

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

    • forecastTypes

      CreateAutoPredictorRequest.Builder forecastTypes(String... forecastTypes)

      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.

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

    • forecastDimensions

      CreateAutoPredictorRequest.Builder forecastDimensions(Collection<String> forecastDimensions)

      An array of dimension (field) names that specify how to group the generated forecast.

      For example, if you are generating forecasts for item sales across all your stores, and your dataset contains a store_id field, you would specify store_id as a dimension to group sales forecasts for each store.

      Parameters:
      forecastDimensions - An array of dimension (field) names that specify how to group the generated forecast.

      For example, if you are generating forecasts for item sales across all your stores, and your dataset contains a store_id field, you would specify store_id as a dimension to group sales forecasts for each store.

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

    • forecastDimensions

      CreateAutoPredictorRequest.Builder forecastDimensions(String... forecastDimensions)

      An array of dimension (field) names that specify how to group the generated forecast.

      For example, if you are generating forecasts for item sales across all your stores, and your dataset contains a store_id field, you would specify store_id as a dimension to group sales forecasts for each store.

      Parameters:
      forecastDimensions - An array of dimension (field) names that specify how to group the generated forecast.

      For example, if you are generating forecasts for item sales across all your stores, and your dataset contains a store_id field, you would specify store_id as a dimension to group sales forecasts for each store.

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

    • forecastFrequency

      CreateAutoPredictorRequest.Builder forecastFrequency(String forecastFrequency)

      The frequency of predictions in a forecast.

      Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:

      • Minute - 1-59

      • Hour - 1-23

      • Day - 1-6

      • Week - 1-4

      • Month - 1-11

      • Year - 1

      Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".

      The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset frequency.

      When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to the RELATED_TIME_SERIES dataset frequency.

      Parameters:
      forecastFrequency - The frequency of predictions in a forecast.

      Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:

      • Minute - 1-59

      • Hour - 1-23

      • Day - 1-6

      • Week - 1-4

      • Month - 1-11

      • Year - 1

      Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".

      The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset frequency.

      When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to the RELATED_TIME_SERIES dataset frequency.

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

    • dataConfig

      CreateAutoPredictorRequest.Builder dataConfig(DataConfig dataConfig)

      The data configuration for your dataset group and any additional datasets.

      Parameters:
      dataConfig - The data configuration for your dataset group and any additional datasets.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • dataConfig

      default CreateAutoPredictorRequest.Builder dataConfig(Consumer<DataConfig.Builder> dataConfig)

      The data configuration for your dataset group and any additional datasets.

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

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

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

    • encryptionConfig

      CreateAutoPredictorRequest.Builder encryptionConfig(EncryptionConfig encryptionConfig)
      Sets the value of the EncryptionConfig property for this object.
      Parameters:
      encryptionConfig - The new value for the EncryptionConfig property for this object.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • encryptionConfig

      default CreateAutoPredictorRequest.Builder encryptionConfig(Consumer<EncryptionConfig.Builder> encryptionConfig)
      Sets the value of the EncryptionConfig property for this object. 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:

    • referencePredictorArn

      CreateAutoPredictorRequest.Builder referencePredictorArn(String referencePredictorArn)

      The ARN of the predictor to retrain or upgrade. This parameter is only used when retraining or upgrading a predictor. When creating a new predictor, do not specify a value for this parameter.

      When upgrading or retraining a predictor, only specify values for the ReferencePredictorArn and PredictorName. The value for PredictorName must be a unique predictor name.

      Parameters:
      referencePredictorArn - The ARN of the predictor to retrain or upgrade. This parameter is only used when retraining or upgrading a predictor. When creating a new predictor, do not specify a value for this parameter.

      When upgrading or retraining a predictor, only specify values for the ReferencePredictorArn and PredictorName. The value for PredictorName must be a unique predictor name.

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

    • optimizationMetric

      CreateAutoPredictorRequest.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

      CreateAutoPredictorRequest.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:

    • explainPredictor

      CreateAutoPredictorRequest.Builder explainPredictor(Boolean explainPredictor)

      Create an Explainability resource for the predictor.

      Parameters:
      explainPredictor - Create an Explainability resource for the predictor.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • tags

      CreateAutoPredictorRequest.Builder tags(Collection<Tag> tags)

      Optional metadata to help you categorize and organize your predictors. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

      The following restrictions apply to tags:

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

      • Maximum number of tags per resource: 50.

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

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

      • Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.

      • Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values can have this prefix. If a tag value has aws as its prefix but the key does not, 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. You cannot edit or delete tag keys with this prefix.

      Parameters:
      tags - Optional metadata to help you categorize and organize your predictors. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

      The following restrictions apply to tags:

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

      • Maximum number of tags per resource: 50.

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

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

      • Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.

      • Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values can have this prefix. If a tag value has aws as its prefix but the key does not, 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. You cannot edit or delete tag keys with this prefix.

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

    • tags

      CreateAutoPredictorRequest.Builder tags(Tag... tags)

      Optional metadata to help you categorize and organize your predictors. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

      The following restrictions apply to tags:

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

      • Maximum number of tags per resource: 50.

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

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

      • Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.

      • Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values can have this prefix. If a tag value has aws as its prefix but the key does not, 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. You cannot edit or delete tag keys with this prefix.

      Parameters:
      tags - Optional metadata to help you categorize and organize your predictors. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

      The following restrictions apply to tags:

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

      • Maximum number of tags per resource: 50.

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

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

      • Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.

      • Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values can have this prefix. If a tag value has aws as its prefix but the key does not, 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. You cannot edit or delete tag keys with this prefix.

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

    • tags

      CreateAutoPredictorRequest.Builder tags(Consumer<Tag.Builder>... tags)

      Optional metadata to help you categorize and organize your predictors. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

      The following restrictions apply to tags:

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

      • Maximum number of tags per resource: 50.

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

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

      • Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.

      • Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values can have this prefix. If a tag value has aws as its prefix but the key does not, 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. You cannot edit or delete tag keys with this prefix.

      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:

    • monitorConfig

      CreateAutoPredictorRequest.Builder monitorConfig(MonitorConfig monitorConfig)

      The configuration details for predictor monitoring. Provide a name for the monitor resource to enable predictor monitoring.

      Predictor monitoring allows you to see how your predictor's performance changes over time. For more information, see Predictor Monitoring.

      Parameters:
      monitorConfig - The configuration details for predictor monitoring. Provide a name for the monitor resource to enable predictor monitoring.

      Predictor monitoring allows you to see how your predictor's performance changes over time. For more information, see Predictor Monitoring.

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

    • monitorConfig

      default CreateAutoPredictorRequest.Builder monitorConfig(Consumer<MonitorConfig.Builder> monitorConfig)

      The configuration details for predictor monitoring. Provide a name for the monitor resource to enable predictor monitoring.

      Predictor monitoring allows you to see how your predictor's performance changes over time. For more information, see Predictor Monitoring.

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

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

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

    • timeAlignmentBoundary

      CreateAutoPredictorRequest.Builder timeAlignmentBoundary(TimeAlignmentBoundary timeAlignmentBoundary)

      The time boundary Forecast uses to align and aggregate any data that doesn't align with your forecast frequency. Provide the unit of time and the time boundary as a key value pair. For more information on specifying a time boundary, see Specifying a Time Boundary. If you don't provide a time boundary, Forecast uses a set of Default Time Boundaries.

      Parameters:
      timeAlignmentBoundary - The time boundary Forecast uses to align and aggregate any data that doesn't align with your forecast frequency. Provide the unit of time and the time boundary as a key value pair. For more information on specifying a time boundary, see Specifying a Time Boundary. If you don't provide a time boundary, Forecast uses a set of Default Time Boundaries.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • timeAlignmentBoundary

      default CreateAutoPredictorRequest.Builder timeAlignmentBoundary(Consumer<TimeAlignmentBoundary.Builder> timeAlignmentBoundary)

      The time boundary Forecast uses to align and aggregate any data that doesn't align with your forecast frequency. Provide the unit of time and the time boundary as a key value pair. For more information on specifying a time boundary, see Specifying a Time Boundary. If you don't provide a time boundary, Forecast uses a set of Default Time Boundaries.

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

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

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

    • overrideConfiguration

      CreateAutoPredictorRequest.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

      CreateAutoPredictorRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)
      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.