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paws.machine.learning (version 0.9.0)

sagemaker_create_data_quality_job_definition: Creates a definition for a job that monitors data quality and drift

Description

Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker AI Model Monitor.

See https://www.paws-r-sdk.com/docs/sagemaker_create_data_quality_job_definition/ for full documentation.

Usage

sagemaker_create_data_quality_job_definition(
  JobDefinitionName,
  DataQualityBaselineConfig = NULL,
  DataQualityAppSpecification,
  DataQualityJobInput,
  DataQualityJobOutputConfig,
  JobResources,
  NetworkConfig = NULL,
  RoleArn,
  StoppingCondition = NULL,
  Tags = NULL
)

Arguments

JobDefinitionName

[required] The name for the monitoring job definition.

DataQualityBaselineConfig

Configures the constraints and baselines for the monitoring job.

DataQualityAppSpecification

[required] Specifies the container that runs the monitoring job.

DataQualityJobInput

[required] A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.

DataQualityJobOutputConfig

[required]

JobResources

[required]

NetworkConfig

Specifies networking configuration for the monitoring job.

RoleArn

[required] The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

StoppingCondition

Tags

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.