CreateAutoMLJob
Creates an Autopilot job.
Find the best performing model after you run an Autopilot job by calling DescribeAutoMLJob. Deploy that model by following the steps described in Step 6.1: Deploy the Model to Amazon SageMaker Hosting Services.
For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.
Request Syntax
{
"AutoMLJobConfig": {
"CompletionCriteria": {
"MaxAutoMLJobRuntimeInSeconds": number
,
"MaxCandidates": number
,
"MaxRuntimePerTrainingJobInSeconds": number
},
"SecurityConfig": {
"EnableInterContainerTrafficEncryption": boolean
,
"VolumeKmsKeyId": "string
",
"VpcConfig": {
"SecurityGroupIds": [ "string
" ],
"Subnets": [ "string
" ]
}
}
},
"AutoMLJobName": "string
",
"AutoMLJobObjective": {
"MetricName": "string
"
},
"GenerateCandidateDefinitionsOnly": boolean
,
"InputDataConfig": [
{
"CompressionType": "string
",
"DataSource": {
"S3DataSource": {
"S3DataType": "string
",
"S3Uri": "string
"
}
},
"TargetAttributeName": "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
-
Contains CompletionCriteria and SecurityConfig.
Type: AutoMLJobConfig object
Required: No
- AutoMLJobName
-
Identifies an Autopilot job. 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 of a an AutoML job. You provide a AutoMLJobObjective:MetricName and Autopilot infers whether to minimize or maximize it. If a metric is not specified, the most commonly used ObjectiveMetric for problem type is automaically selected.
Type: AutoMLJobObjective object
Required: No
- GenerateCandidateDefinitionsOnly
-
Generates possible candidates without training a model. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
Type: Boolean
Required: No
- InputDataConfig
-
Similar to InputDataConfig supported by Tuning. Format(s) supported: CSV. Minimum of 500 rows.
Type: Array of AutoMLChannel objects
Array Members: Minimum number of 1 item. Maximum number of 20 items.
Required: Yes
- OutputDataConfig
-
Similar to OutputDataConfig supported by Tuning. Format(s) supported: CSV.
Type: AutoMLOutputDataConfig object
Required: Yes
- ProblemType
-
Defines the kind of preprocessing and algorithms intended for the candidates. Options include: BinaryClassification, MulticlassClassification, and Regression.
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
-
Each tag consists of a key and an optional value. 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
-
When a job is created, it is assigned a unique ARN.
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 Amazon SageMaker resource limit. For example, you might have too many training jobs created.
HTTP Status Code: 400
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following: