sagemaker/aws.sdk.kotlin.services.sagemaker.model/CreateAutoMlJobRequest/Builder

Builder

class Builder

Properties

autoMlJobConfig

var autoMlJobConfig: AutoMlJobConfig?

A collection of settings used to configure an AutoML job.

autoMlJobName

var autoMlJobName: String?

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

autoMlJobObjective

var autoMlJobObjective: AutoMlJobObjective?

Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.

generateCandidateDefinitionsOnly

var generateCandidateDefinitionsOnly: Boolean?

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

inputDataConfig

var inputDataConfig: List<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 HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.

modelDeployConfig

var modelDeployConfig: ModelDeployConfig?

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

outputDataConfig

var outputDataConfig: AutoMlOutputDataConfig?

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

problemType

var problemType: ProblemType?

Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.

roleArn

var roleArn: String?

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