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
}, # OPTIONAL
GenerateCandidateDefinitionsOnly => 1, # 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.
REQUIRED AutoMLJobName => Str
Identifies an AutoPilot job. Must be unique to your account and is case-insensitive.
AutoMLJobObjective => Paws::SageMaker::AutoMLJobObjective
Defines the job's objective. You provide a MetricName and AutoML will infer minimize or maximize. If this is not provided, the most commonly used ObjectiveMetric for problem type will be selected.
GenerateCandidateDefinitionsOnly => Bool
This will generate possible candidates without training a model. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
REQUIRED InputDataConfig => ArrayRef[Paws::SageMaker::AutoMLChannel]
Similar to InputDataConfig supported by Tuning. Format(s) supported: CSV.
REQUIRED OutputDataConfig => Paws::SageMaker::AutoMLOutputDataConfig
Similar to OutputDataConfig supported by Tuning. Format(s) supported: CSV.
ProblemType => Str
Defines the kind of preprocessing and algorithms intended for the candidates. Options include: BinaryClassification, MulticlassClassification, and Regression.
Valid values are: "BinaryClassification", "MulticlassClassification", "Regression"
REQUIRED RoleArn => Str
The ARN of the role that will be 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