sagemaker_create_model_explainability_job_definition: Creates the definition for a model explainability job

View source: R/sagemaker_operations.R

sagemaker_create_model_explainability_job_definitionR Documentation

Creates the definition for a model explainability job

Description

Creates the definition for a model explainability job.

See https://www.paws-r-sdk.com/docs/sagemaker_create_model_explainability_job_definition/ for full documentation.

Usage

sagemaker_create_model_explainability_job_definition(
  JobDefinitionName,
  ModelExplainabilityBaselineConfig = NULL,
  ModelExplainabilityAppSpecification,
  ModelExplainabilityJobInput,
  ModelExplainabilityJobOutputConfig,
  JobResources,
  NetworkConfig = NULL,
  RoleArn,
  StoppingCondition = NULL,
  Tags = NULL
)

Arguments

JobDefinitionName

[required] The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.

ModelExplainabilityBaselineConfig

The baseline configuration for a model explainability job.

ModelExplainabilityAppSpecification

[required] Configures the model explainability job to run a specified Docker container image.

ModelExplainabilityJobInput

[required] Inputs for the model explainability job.

ModelExplainabilityJobOutputConfig

[required]

JobResources

[required]

NetworkConfig

Networking options for a model explainability job.

RoleArn

[required] The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

StoppingCondition
Tags

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.


paws.machine.learning documentation built on Sept. 12, 2024, 6:23 a.m.