public static interface CreateAutoMlJobRequest.Builder extends SageMakerRequest.Builder, SdkPojo, CopyableBuilder<CreateAutoMlJobRequest.Builder,CreateAutoMlJobRequest>
| Modifier and Type | Method and Description |
|---|---|
CreateAutoMlJobRequest.Builder |
autoMLJobConfig(AutoMLJobConfig autoMLJobConfig)
A collection of settings used to configure an AutoML job.
|
default CreateAutoMlJobRequest.Builder |
autoMLJobConfig(Consumer<AutoMLJobConfig.Builder> autoMLJobConfig)
A collection of settings used to configure an AutoML job.
|
CreateAutoMlJobRequest.Builder |
autoMLJobName(String autoMLJobName)
Identifies an Autopilot job.
|
CreateAutoMlJobRequest.Builder |
autoMLJobObjective(AutoMLJobObjective autoMLJobObjective)
Defines the objective metric used to measure the predictive quality of an AutoML job.
|
default CreateAutoMlJobRequest.Builder |
autoMLJobObjective(Consumer<AutoMLJobObjective.Builder> autoMLJobObjective)
Defines the objective metric used to measure the predictive quality of an AutoML job.
|
CreateAutoMlJobRequest.Builder |
generateCandidateDefinitionsOnly(Boolean generateCandidateDefinitionsOnly)
Generates possible candidates without training the models.
|
CreateAutoMlJobRequest.Builder |
inputDataConfig(AutoMLChannel... inputDataConfig)
An array of channel objects that describes the input data and its location.
|
CreateAutoMlJobRequest.Builder |
inputDataConfig(Collection<AutoMLChannel> inputDataConfig)
An array of channel objects that describes the input data and its location.
|
CreateAutoMlJobRequest.Builder |
inputDataConfig(Consumer<AutoMLChannel.Builder>... inputDataConfig)
An array of channel objects that describes the input data and its location.
|
default CreateAutoMlJobRequest.Builder |
modelDeployConfig(Consumer<ModelDeployConfig.Builder> modelDeployConfig)
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
|
CreateAutoMlJobRequest.Builder |
modelDeployConfig(ModelDeployConfig modelDeployConfig)
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
|
CreateAutoMlJobRequest.Builder |
outputDataConfig(AutoMLOutputDataConfig outputDataConfig)
Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML
job.
|
default CreateAutoMlJobRequest.Builder |
outputDataConfig(Consumer<AutoMLOutputDataConfig.Builder> outputDataConfig)
Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML
job.
|
CreateAutoMlJobRequest.Builder |
overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) |
CreateAutoMlJobRequest.Builder |
overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) |
CreateAutoMlJobRequest.Builder |
problemType(ProblemType problemType)
Defines the type of supervised learning available for the candidates.
|
CreateAutoMlJobRequest.Builder |
problemType(String problemType)
Defines the type of supervised learning available for the candidates.
|
CreateAutoMlJobRequest.Builder |
roleArn(String roleArn)
The ARN of the role that is used to access the data.
|
CreateAutoMlJobRequest.Builder |
tags(Collection<Tag> tags)
Each tag consists of a key and an optional value.
|
CreateAutoMlJobRequest.Builder |
tags(Consumer<Tag.Builder>... tags)
Each tag consists of a key and an optional value.
|
CreateAutoMlJobRequest.Builder |
tags(Tag... tags)
Each tag consists of a key and an optional value.
|
buildoverrideConfigurationequalsBySdkFields, sdkFieldscopyapplyMutation, buildCreateAutoMlJobRequest.Builder autoMLJobName(String autoMLJobName)
Identifies an Autopilot job. The name must be unique to your account and is case-insensitive.
autoMLJobName - Identifies an Autopilot job. The name must be unique to your account and is case-insensitive.CreateAutoMlJobRequest.Builder inputDataConfig(Collection<AutoMLChannel> inputDataConfig)
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, 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.
inputDataConfig - 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,
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.CreateAutoMlJobRequest.Builder inputDataConfig(AutoMLChannel... inputDataConfig)
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, 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.
inputDataConfig - 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,
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.CreateAutoMlJobRequest.Builder inputDataConfig(Consumer<AutoMLChannel.Builder>... inputDataConfig)
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, 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.
AutoMLChannel.Builder avoiding the need to create one
manually via AutoMLChannel.builder().
When the Consumer completes,
SdkBuilder.build() is called immediately
and its result is passed to #inputDataConfig(List.
inputDataConfig - a consumer that will call methods on
AutoMLChannel.Builder#inputDataConfig(java.util.Collection) CreateAutoMlJobRequest.Builder outputDataConfig(AutoMLOutputDataConfig outputDataConfig)
Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
outputDataConfig - Provides information about encryption and the Amazon S3 output path needed to store artifacts from an
AutoML job. Format(s) supported: CSV.default CreateAutoMlJobRequest.Builder outputDataConfig(Consumer<AutoMLOutputDataConfig.Builder> outputDataConfig)
Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
This is a convenience method that creates an instance of theAutoMLOutputDataConfig.Builder avoiding
the need to create one manually via AutoMLOutputDataConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and
its result is passed to outputDataConfig(AutoMLOutputDataConfig).
outputDataConfig - a consumer that will call methods on AutoMLOutputDataConfig.BuilderoutputDataConfig(AutoMLOutputDataConfig)CreateAutoMlJobRequest.Builder problemType(String problemType)
Defines the type of supervised learning available for the candidates. For more information, see Amazon SageMaker Autopilot problem types and algorithm support.
problemType - Defines the type of supervised learning available for the candidates. For more information, see Amazon SageMaker Autopilot problem types and algorithm support.ProblemType,
ProblemTypeCreateAutoMlJobRequest.Builder problemType(ProblemType problemType)
Defines the type of supervised learning available for the candidates. For more information, see Amazon SageMaker Autopilot problem types and algorithm support.
problemType - Defines the type of supervised learning available for the candidates. For more information, see Amazon SageMaker Autopilot problem types and algorithm support.ProblemType,
ProblemTypeCreateAutoMlJobRequest.Builder autoMLJobObjective(AutoMLJobObjective autoMLJobObjective)
Defines the objective metric used to measure the predictive quality of an AutoML job. You provide an AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or maximize it.
autoMLJobObjective - Defines the objective metric used to measure the predictive quality of an AutoML job. You provide an
AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or maximize it.default CreateAutoMlJobRequest.Builder autoMLJobObjective(Consumer<AutoMLJobObjective.Builder> 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.
This is a convenience method that creates an instance of theAutoMLJobObjective.Builder avoiding the
need to create one manually via AutoMLJobObjective.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to autoMLJobObjective(AutoMLJobObjective).
autoMLJobObjective - a consumer that will call methods on AutoMLJobObjective.BuilderautoMLJobObjective(AutoMLJobObjective)CreateAutoMlJobRequest.Builder autoMLJobConfig(AutoMLJobConfig autoMLJobConfig)
A collection of settings used to configure an AutoML job.
autoMLJobConfig - A collection of settings used to configure an AutoML job.default CreateAutoMlJobRequest.Builder autoMLJobConfig(Consumer<AutoMLJobConfig.Builder> autoMLJobConfig)
A collection of settings used to configure an AutoML job.
This is a convenience method that creates an instance of theAutoMLJobConfig.Builder avoiding the
need to create one manually via AutoMLJobConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to autoMLJobConfig(AutoMLJobConfig).
autoMLJobConfig - a consumer that will call methods on AutoMLJobConfig.BuilderautoMLJobConfig(AutoMLJobConfig)CreateAutoMlJobRequest.Builder roleArn(String roleArn)
The ARN of the role that is used to access the data.
roleArn - The ARN of the role that is used to access the data.CreateAutoMlJobRequest.Builder generateCandidateDefinitionsOnly(Boolean generateCandidateDefinitionsOnly)
Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
generateCandidateDefinitionsOnly - Generates possible candidates without training the models. A candidate is a combination of data
preprocessors, algorithms, and algorithm parameter settings.CreateAutoMlJobRequest.Builder tags(Collection<Tag> tags)
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
tags - Each tag consists of a key and an optional value. Tag keys must be unique per resource.CreateAutoMlJobRequest.Builder tags(Tag... tags)
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
tags - Each tag consists of a key and an optional value. Tag keys must be unique per resource.CreateAutoMlJobRequest.Builder tags(Consumer<Tag.Builder>... tags)
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
This is a convenience method that creates an instance of theTag.Builder avoiding the need to create one manually
via Tag.builder().
When the Consumer completes,
SdkBuilder.build() is called immediately and its
result is passed to #tags(List.
tags - a consumer that will call methods on
Tag.Builder#tags(java.util.Collection) CreateAutoMlJobRequest.Builder modelDeployConfig(ModelDeployConfig modelDeployConfig)
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
modelDeployConfig - Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.default CreateAutoMlJobRequest.Builder modelDeployConfig(Consumer<ModelDeployConfig.Builder> modelDeployConfig)
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
This is a convenience method that creates an instance of theModelDeployConfig.Builder avoiding the
need to create one manually via ModelDeployConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to modelDeployConfig(ModelDeployConfig).
modelDeployConfig - a consumer that will call methods on ModelDeployConfig.BuildermodelDeployConfig(ModelDeployConfig)CreateAutoMlJobRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)
overrideConfiguration in interface AwsRequest.BuilderCreateAutoMlJobRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)
overrideConfiguration in interface AwsRequest.BuilderCopyright © 2022. All rights reserved.