MlTransform
A structure for a machine learning transform.
Types
Properties
A user-defined, long-form description text for the machine learning transform. Descriptions are not guaranteed to be unique and can be changed at any time.
An EvaluationMetrics
object. Evaluation metrics provide an estimate of the quality of your machine learning transform.
This value determines which version of Glue this machine learning transform is compatible with. Glue 1.0 is recommended for most customers. If the value is not set, the Glue compatibility defaults to Glue 0.9. For more information, see Glue Versions in the developer guide.
A list of Glue table definitions used by the transform.
A count identifier for the labeling files generated by Glue for this transform. As you create a better transform, you can iteratively download, label, and upload the labeling file.
A timestamp. The last point in time when this machine learning transform was modified.
The number of Glue data processing units (DPUs) that are allocated to task runs for this transform. You can allocate from 2 to 100 DPUs; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
The maximum number of times to retry after an MLTaskRun
of the machine learning transform fails.
The number of workers of a defined workerType
that are allocated when a task of the transform runs.
A TransformParameters
object. You can use parameters to tune (customize) the behavior of the machine learning transform by specifying what data it learns from and your preference on various tradeoffs (such as precious vs. recall, or accuracy vs. cost).
A map of key-value pairs representing the columns and data types that this transform can run against. Has an upper bound of 100 columns.
The current status of the machine learning transform.
The encryption-at-rest settings of the transform that apply to accessing user data. Machine learning transforms can access user data encrypted in Amazon S3 using KMS.
The unique transform ID that is generated for the machine learning transform. The ID is guaranteed to be unique and does not change.
The type of predefined worker that is allocated when a task of this transform runs. Accepts a value of Standard, G.1X, or G.2X.