Request Syntax Request Parameters Response Syntax Response Elements Errors See Also

CreateAutoMLJob

Creates an Autopilot job.

Find the best-performing model after you run an Autopilot job by calling DescribeAutoMLJob.

For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.

Request Syntax


{
   "AutoMLJobConfig": { 
      "CandidateGenerationConfig": { 
         "AlgorithmsConfig": [ 
            { 
               "AutoMLAlgorithms": [ "string" ]
            }
         ],
         "FeatureSpecificationS3Uri": "string"
      },
      "CompletionCriteria": { 
         "MaxAutoMLJobRuntimeInSeconds": number,
         "MaxCandidates": number,
         "MaxRuntimePerTrainingJobInSeconds": number
      },
      "DataSplitConfig": { 
         "ValidationFraction": number
      },
      "Mode": "string",
      "SecurityConfig": { 
         "EnableInterContainerTrafficEncryption": boolean,
         "VolumeKmsKeyId": "string",
         "VpcConfig": { 
            "SecurityGroupIds": [ "string" ],
            "Subnets": [ "string" ]
         }
      }
   },
   "AutoMLJobName": "string",
   "AutoMLJobObjective": { 
      "MetricName": "string"
   },
   "GenerateCandidateDefinitionsOnly": boolean,
   "InputDataConfig": [ 
      { 
         "ChannelType": "string",
         "CompressionType": "string",
         "ContentType": "string",
         "DataSource": { 
            "S3DataSource": { 
               "S3DataType": "string",
               "S3Uri": "string"
            }
         },
         "SampleWeightAttributeName": "string",
         "TargetAttributeName": "string"
      }
   ],
   "ModelDeployConfig": { 
      "AutoGenerateEndpointName": boolean,
      "EndpointName": "string"
   },
   "OutputDataConfig": { 
      "KmsKeyId": "string",
      "S3OutputPath": "string"
   },
   "ProblemType": "string",
   "RoleArn": "string",
   "Tags": [ 
      { 
         "Key": "string",
         "Value": "string"
      }
   ]
}

Request Parameters

For information about the parameters that are common to all actions, see Common Parameters.

The request accepts the following data in JSON format.

AutoMLJobConfig

A collection of settings used to configure an AutoML job.

Type: AutoMLJobConfig object

Required: No

AutoMLJobName

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

Type: String

Length Constraints: Minimum length of 1. Maximum length of 32.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,31}

Required: Yes

AutoMLJobObjective

Defines the objective metric used to measure the predictive quality of an AutoML job. You provide an AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or maximize it. For CreateAutoMLJobV2, only Accuracy is supported.

Type: AutoMLJobObjective object

Required: No

GenerateCandidateDefinitionsOnly

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

Type: Boolean

Required: No

InputDataConfig

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.

Type: Array of AutoMLChannel objects

Array Members: Minimum number of 1 item. Maximum number of 2 items.

Required: Yes

ModelDeployConfig

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

Type: ModelDeployConfig object

Required: No

OutputDataConfig

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

Type: AutoMLOutputDataConfig object

Required: Yes

ProblemType

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

Type: String

Valid Values: BinaryClassification | MulticlassClassification | Regression

Required: No

RoleArn

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

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws[a-z\-]*:iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+$

Required: Yes

Tags

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

Type: Array of Tag objects

Array Members: Minimum number of 0 items. Maximum number of 50 items.

Required: No

Response Syntax


{
   "AutoMLJobArn": "string"
}

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.

AutoMLJobArn

The unique ARN assigned to the AutoML job when it is created.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 256.

Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:automl-job/.*

Errors

For information about the errors that are common to all actions, see Common Errors.

ResourceInUse

Resource being accessed is in use.

HTTP Status Code: 400

ResourceLimitExceeded

You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.

HTTP Status Code: 400