/ 
Paws-0.46
River stage two • 9 direct dependents • 11 total dependents
/ Paws::SageMaker::CreateAutoMLJob

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.

SEE ALSO

This class forms part of Paws, documenting arguments for method CreateAutoMLJob in Paws::SageMaker

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