package Paws::SageMaker::CreateAutoMLJob; use Moose; has AutoMLJobConfig => (is => 'ro', isa => 'Paws::SageMaker::AutoMLJobConfig'); has AutoMLJobName => (is => 'ro', isa => 'Str', required => 1); has AutoMLJobObjective => (is => 'ro', isa => 'Paws::SageMaker::AutoMLJobObjective'); has GenerateCandidateDefinitionsOnly => (is => 'ro', isa => 'Bool'); has InputDataConfig => (is => 'ro', isa => 'ArrayRef[Paws::SageMaker::AutoMLChannel]', required => 1); has ModelDeployConfig => (is => 'ro', isa => 'Paws::SageMaker::ModelDeployConfig'); has OutputDataConfig => (is => 'ro', isa => 'Paws::SageMaker::AutoMLOutputDataConfig', required => 1); has ProblemType => (is => 'ro', isa => 'Str'); has RoleArn => (is => 'ro', isa => 'Str', required => 1); has Tags => (is => 'ro', isa => 'ArrayRef[Paws::SageMaker::Tag]'); use MooseX::ClassAttribute; class_has _api_call => (isa => 'Str', is => 'ro', default => 'CreateAutoMLJob'); class_has _returns => (isa => 'Str', is => 'ro', default => 'Paws::SageMaker::CreateAutoMLJobResponse'); class_has _result_key => (isa => 'Str', is => 'ro'); 1; ### main pod documentation begin ### =head1 NAME Paws::SageMaker::CreateAutoMLJob - Arguments for method CreateAutoMLJob on L =head1 DESCRIPTION This class represents the parameters used for calling the method CreateAutoMLJob on the L 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. =head1 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 = $CreateAutoMLJobResponse->AutoMLJobArn; # Returns a L object. Values for attributes that are native types (Int, String, Float, etc) can passed as-is (scalar values). Values for complex Types (objects) can be passed as a HashRef. The keys and values of the hashref will be used to instance the underlying object. For the AWS API documentation, see L =head1 ATTRIBUTES =head2 AutoMLJobConfig => L Contains C and C settings for the AutoML job. =head2 B AutoMLJobName => Str Identifies an Autopilot job. The name must be unique to your account and is case-insensitive. =head2 AutoMLJobObjective => L Defines the objective metric used to measure the predictive quality of an AutoML job. You provide an AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or maximize it. =head2 GenerateCandidateDefinitionsOnly => Bool Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings. =head2 B InputDataConfig => ArrayRef[L] An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to C supported by . Format(s) supported: CSV. Minimum of 500 rows. =head2 ModelDeployConfig => L Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment. =head2 B OutputDataConfig => L Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV. =head2 ProblemType => Str Defines the type of supervised learning available for the candidates. Options include: C, C, and C. 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: C<"BinaryClassification">, C<"MulticlassClassification">, C<"Regression"> =head2 B RoleArn => Str The ARN of the role that is used to access the data. =head2 Tags => ArrayRef[L] Each tag consists of a key and an optional value. Tag keys must be unique per resource. =head1 SEE ALSO This class forms part of L, documenting arguments for method CreateAutoMLJob in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut