Glue / Client / start_ml_labeling_set_generation_task_run
start_ml_labeling_set_generation_task_run#
- Glue.Client.start_ml_labeling_set_generation_task_run(**kwargs)#
Starts the active learning workflow for your machine learning transform to improve the transform’s quality by generating label sets and adding labels.
When the
StartMLLabelingSetGenerationTaskRun
finishes, Glue will have generated a “labeling set” or a set of questions for humans to answer.In the case of the
FindMatches
transform, these questions are of the form, “What is the correct way to group these rows together into groups composed entirely of matching records?”After the labeling process is finished, you can upload your labels with a call to
StartImportLabelsTaskRun
. AfterStartImportLabelsTaskRun
finishes, all future runs of the machine learning transform will use the new and improved labels and perform a higher-quality transformation.See also: AWS API Documentation
Request Syntax
response = client.start_ml_labeling_set_generation_task_run( TransformId='string', OutputS3Path='string' )
- Parameters:
TransformId (string) –
[REQUIRED]
The unique identifier of the machine learning transform.
OutputS3Path (string) –
[REQUIRED]
The Amazon Simple Storage Service (Amazon S3) path where you generate the labeling set.
- Return type:
dict
- Returns:
Response Syntax
{ 'TaskRunId': 'string' }
Response Structure
(dict) –
TaskRunId (string) –
The unique run identifier that is associated with this task run.
Exceptions
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.OperationTimeoutException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.ConcurrentRunsExceededException