class Aws::SageMaker::Types::CreateAutoMLJobRequest

@note When making an API call, you may pass CreateAutoMLJobRequest

data as a hash:

    {
      auto_ml_job_name: "AutoMLJobName", # required
      input_data_config: [ # required
        {
          data_source: { # required
            s3_data_source: { # required
              s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix
              s3_uri: "S3Uri", # required
            },
          },
          compression_type: "None", # accepts None, Gzip
          target_attribute_name: "TargetAttributeName", # required
        },
      ],
      output_data_config: { # required
        kms_key_id: "KmsKeyId",
        s3_output_path: "S3Uri", # required
      },
      problem_type: "BinaryClassification", # accepts BinaryClassification, MulticlassClassification, Regression
      auto_ml_job_objective: {
        metric_name: "Accuracy", # required, accepts Accuracy, MSE, F1, F1macro, AUC
      },
      auto_ml_job_config: {
        completion_criteria: {
          max_candidates: 1,
          max_runtime_per_training_job_in_seconds: 1,
          max_auto_ml_job_runtime_in_seconds: 1,
        },
        security_config: {
          volume_kms_key_id: "KmsKeyId",
          enable_inter_container_traffic_encryption: false,
          vpc_config: {
            security_group_ids: ["SecurityGroupId"], # required
            subnets: ["SubnetId"], # required
          },
        },
      },
      role_arn: "RoleArn", # required
      generate_candidate_definitions_only: false,
      tags: [
        {
          key: "TagKey", # required
          value: "TagValue", # required
        },
      ],
      model_deploy_config: {
        auto_generate_endpoint_name: false,
        endpoint_name: "EndpointName",
      },
    }

@!attribute [rw] auto_ml_job_name

Identifies an Autopilot job. The name must be unique to your account
and is case-insensitive.
@return [String]

@!attribute [rw] input_data_config

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 . Format(s) supported: CSV. Minimum
of 500 rows.
@return [Array<Types::AutoMLChannel>]

@!attribute [rw] output_data_config

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

@!attribute [rw] problem_type

Defines the type of supervised learning available for the
candidates. Options include: `BinaryClassification`,
`MulticlassClassification`, and `Regression`. For more information,
see [ Amazon SageMaker Autopilot problem types and algorithm
support][1].

[1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-problem-types.html
@return [String]

@!attribute [rw] auto_ml_job_objective

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.
@return [Types::AutoMLJobObjective]

@!attribute [rw] auto_ml_job_config

Contains `CompletionCriteria` and `SecurityConfig` settings for the
AutoML job.
@return [Types::AutoMLJobConfig]

@!attribute [rw] role_arn

The ARN of the role that is used to access the data.
@return [String]

@!attribute [rw] generate_candidate_definitions_only

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

@!attribute [rw] tags

Each tag consists of a key and an optional value. Tag keys must be
unique per resource.
@return [Array<Types::Tag>]

@!attribute [rw] model_deploy_config

Specifies how to generate the endpoint name for an automatic
one-click Autopilot model deployment.
@return [Types::ModelDeployConfig]

@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAutoMLJobRequest AWS API Documentation

Constants

SENSITIVE