NAME

Paws::SageMaker::CreateAutoMLJob - Arguments for method CreateAutoMLJob on Paws::SageMaker

DESCRIPTION

This class represents the parameters used for calling the method CreateAutoMLJob on the Amazon SageMaker Service service. Use the attributes of this class as arguments to method CreateAutoMLJob.

You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to CreateAutoMLJob.

SYNOPSIS

    my $api.sagemaker = Paws->service('SageMaker');
    my $CreateAutoMLJobResponse = $api . sagemaker->CreateAutoMLJob(
      AutoMLJobName   => 'MyAutoMLJobName',
      InputDataConfig => [
        {
          DataSource => {
            S3DataSource => {
              S3DataType => 'ManifestFile',    # values: ManifestFile, S3Prefix
              S3Uri      => 'MyS3Uri',         # max: 1024
            },
          },
          TargetAttributeName => 'MyTargetAttributeName',    # min: 1
          CompressionType     => 'None',    # values: None, Gzip; OPTIONAL
        },
        ...
      ],
      OutputDataConfig => {
        S3OutputPath => 'MyS3Uri',       # max: 1024
        KmsKeyId     => 'MyKmsKeyId',    # max: 2048; OPTIONAL
      },
      RoleArn         => 'MyRoleArn',
      AutoMLJobConfig => {
        CompletionCriteria => {
          MaxAutoMLJobRuntimeInSeconds      => 1,    # min: 1; OPTIONAL
          MaxCandidates                     => 1,    # min: 1; OPTIONAL
          MaxRuntimePerTrainingJobInSeconds => 1,    # min: 1; OPTIONAL
        },    # OPTIONAL
        SecurityConfig => {
          EnableInterContainerTrafficEncryption => 1,    # OPTIONAL
          VolumeKmsKeyId => 'MyKmsKeyId',                # max: 2048; OPTIONAL
          VpcConfig      => {
            SecurityGroupIds => [
              'MySecurityGroupId', ...                   # max: 32
            ],    # min: 1, max: 5
            Subnets => [
              'MySubnetId', ...    # max: 32
            ],    # min: 1, max: 16
          },    # OPTIONAL
        },    # OPTIONAL
      },    # OPTIONAL
      AutoMLJobObjective => {
        MetricName => 'Accuracy',    # values: Accuracy, MSE, F1, F1macro, AUC
      },    # OPTIONAL
      GenerateCandidateDefinitionsOnly => 1,    # OPTIONAL
      ModelDeployConfig                => {
        AutoGenerateEndpointName => 1,                   # OPTIONAL
        EndpointName             => 'MyEndpointName',    # max: 63; OPTIONAL
      },    # OPTIONAL
      ProblemType => 'BinaryClassification',    # OPTIONAL
      Tags        => [
        {
          Key   => 'MyTagKey',      # min: 1, max: 128
          Value => 'MyTagValue',    # max: 256
        },
        ...
      ],    # OPTIONAL
    );
    # Results:
    my $AutoMLJobArn = $CreateAutoMLJobResponse->AutoMLJobArn;
    # Returns a L<Paws::SageMaker::CreateAutoMLJobResponse> object.

Values for attributes that are native types (Int, String, Float, etc) can passed as-is (scalar values). Values for complex Types (objects) can be passed as a HashRef. The keys and values of the hashref will be used to instance the underlying object. For the AWS API documentation, see <https://docs.aws.amazon.com/goto/WebAPI/api.sagemaker/CreateAutoMLJob>

ATTRIBUTES

AutoMLJobConfig => Paws::SageMaker::AutoMLJobConfig

Contains "CompletionCriteria" and "SecurityConfig" settings for the AutoML job.

REQUIRED AutoMLJobName => Str

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

AutoMLJobObjective => Paws::SageMaker::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.

GenerateCandidateDefinitionsOnly => Bool

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

REQUIRED InputDataConfig => ArrayRef[Paws::SageMaker::AutoMLChannel]

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.

ModelDeployConfig => Paws::SageMaker::ModelDeployConfig

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

REQUIRED OutputDataConfig => Paws::SageMaker::AutoMLOutputDataConfig

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

ProblemType => Str

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 (https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-problem-types.html).

Valid values are: "BinaryClassification", "MulticlassClassification", "Regression"

REQUIRED RoleArn => Str

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

Tags => ArrayRef[Paws::SageMaker::Tag]

Each tag consists of a key and an optional value. Tag keys must be unique per resource.

BUGS and CONTRIBUTIONS

The source code is located here: <https://github.com/pplu/aws-sdk-perl>

Please report bugs to: <https://github.com/pplu/aws-sdk-perl/issues>