/AWS1/CL_SGM=>CREATEAUTOMLJOB()

About CreateAutoMLJob

Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.

We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.

CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).

Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.

You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.

Method Signature

IMPORTING

Required arguments:

IV_AUTOMLJOBNAME TYPE /AWS1/SGMAUTOMLJOBNAME /AWS1/SGMAUTOMLJOBNAME

Identifies an Autopilot job. The name must be unique to your account and is case insensitive.

IT_INPUTDATACONFIG TYPE /AWS1/CL_SGMAUTOMLCHANNEL=>TT_AUTOMLINPUTDATACONFIG TT_AUTOMLINPUTDATACONFIG

An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

IO_OUTPUTDATACONFIG TYPE REF TO /AWS1/CL_SGMAUTOMLOUTDATACFG /AWS1/CL_SGMAUTOMLOUTDATACFG

Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.

IV_ROLEARN TYPE /AWS1/SGMROLEARN /AWS1/SGMROLEARN

The ARN of the role that is used to access the data.

Optional arguments:

IV_PROBLEMTYPE TYPE /AWS1/SGMPROBLEMTYPE /AWS1/SGMPROBLEMTYPE

Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.

IO_AUTOMLJOBOBJECTIVE TYPE REF TO /AWS1/CL_SGMAUTOMLJOBOBJECTIVE /AWS1/CL_SGMAUTOMLJOBOBJECTIVE

Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.

IO_AUTOMLJOBCONFIG TYPE REF TO /AWS1/CL_SGMAUTOMLJOBCONFIG /AWS1/CL_SGMAUTOMLJOBCONFIG

A collection of settings used to configure an AutoML job.

IV_GENERATECANDIDATEDEFNSO00 TYPE /AWS1/SGMGENERATECANDIDATEDE00 /AWS1/SGMGENERATECANDIDATEDE00

Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.

IT_TAGS TYPE /AWS1/CL_SGMTAG=>TT_TAGLIST TT_TAGLIST

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.

IO_MODELDEPLOYCONFIG TYPE REF TO /AWS1/CL_SGMMODELDEPLOYCONFIG /AWS1/CL_SGMMODELDEPLOYCONFIG

Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

RETURNING

OO_OUTPUT TYPE REF TO /AWS1/CL_SGMCREATEAUTOMLJOBRSP /AWS1/CL_SGMCREATEAUTOMLJOBRSP