Package software.amazon.awssdk.services.lookoutequipment.model

Interface CreateRetrainingSchedulerRequest.Builder

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

  • Method Details

    • modelName

      CreateRetrainingSchedulerRequest.Builder modelName(String modelName)

      The name of the model to add the retraining scheduler to.

      Parameters:
      modelName - The name of the model to add the retraining scheduler to.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • retrainingStartDate

      CreateRetrainingSchedulerRequest.Builder retrainingStartDate(Instant retrainingStartDate)

      The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

      Parameters:
      retrainingStartDate - The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • retrainingFrequency

      CreateRetrainingSchedulerRequest.Builder retrainingFrequency(String retrainingFrequency)

      This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid:

      • P3M15D – Every 3 months and 15 days

      • P2M – Every 2 months

      • P150D – Every 150 days

      Parameters:
      retrainingFrequency - This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid:

      • P3M15D – Every 3 months and 15 days

      • P2M – Every 2 months

      • P150D – Every 150 days

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

    • lookbackWindow

      CreateRetrainingSchedulerRequest.Builder lookbackWindow(String lookbackWindow)

      The number of past days of data that will be used for retraining.

      Parameters:
      lookbackWindow - The number of past days of data that will be used for retraining.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • promoteMode

      CreateRetrainingSchedulerRequest.Builder promoteMode(String promoteMode)

      Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated.

      Parameters:
      promoteMode - Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated.
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:

    • promoteMode

      CreateRetrainingSchedulerRequest.Builder promoteMode(ModelPromoteMode promoteMode)

      Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated.

      Parameters:
      promoteMode - Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated.
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:

    • clientToken

      CreateRetrainingSchedulerRequest.Builder clientToken(String clientToken)

      A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

      Parameters:
      clientToken - A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • overrideConfiguration

      CreateRetrainingSchedulerRequest.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

      CreateRetrainingSchedulerRequest.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.