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

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

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 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 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.

paws.machine.learning documentation built on Sept. 12, 2024, 6:23 a.m.