Amazon Forecast Service¶

Description¶

Provides APIs for creating and managing Amazon Forecast resources.

Usage¶

forecastservice(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments¶

config

Optional configuration of credentials, endpoint, and/or region.
- credentials:
  - creds:
    - access_key_id: AWS access key ID
    - secret_access_key: AWS secret access key
    - session_token: AWS temporary session token
  - profile: The name of a profile to use. If not given, then the default profile is used.
  - anonymous: Set anonymous credentials.
- endpoint: The complete URL to use for the constructed client.
- region: The AWS Region used in instantiating the client.
- close_connection: Immediately close all HTTP connections.
- timeout: The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds.
- s3_force_path_style: Set this to true to force the request to use path-style addressing, i.e. http://s3.amazonaws.com/BUCKET/KEY.
- sts_regional_endpoint: Set sts regional endpoint resolver to regional or legacy https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html
- use_dual_stack: Set this to true to use the dualstack (IPv4 and IPv6) endpoint for a service, where available, falling back to the regular endpoint when it isn't. Defaults to the AWS_USE_DUALSTACK_ENDPOINT environment variable when unset.
credentials

Optional credentials shorthand for the config parameter
- creds:
  - access_key_id: AWS access key ID
  - secret_access_key: AWS secret access key
  - session_token: AWS temporary session token
- profile: The name of a profile to use. If not given, then the default profile is used.
- anonymous: Set anonymous credentials.
endpoint

Optional shorthand for complete URL to use for the constructed client.
region

Optional shorthand for AWS Region used in instantiating the client.

Value¶

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax¶

svc <- forecastservice(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string",
    use_dual_stack = "logical"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations¶

`create_auto_predictor`	Creates an Amazon Forecast predictor
`create_dataset`	Creates an Amazon Forecast dataset
`create_dataset_group`	Creates a dataset group, which holds a collection of related datasets
`create_dataset_import_job`	Imports your training data to an Amazon Forecast dataset
`create_explainability`	Explainability is only available for Forecasts and Predictors generated from an AutoPredictor (CreateAutoPredictor)
`create_explainability_export`	Exports an Explainability resource created by the CreateExplainability operation
`create_forecast`	Creates a forecast for each item in the TARGET_TIME_SERIES dataset that was used to train the predictor
`create_forecast_export_job`	Exports a forecast created by the CreateForecast operation to your Amazon Simple Storage Service (Amazon S3) bucket
`create_monitor`	Creates a predictor monitor resource for an existing auto predictor
`create_predictor`	This operation creates a legacy predictor that does not include all the predictor functionalities provided by Amazon Forecast
`create_predictor_backtest_export_job`	Exports backtest forecasts and accuracy metrics generated by the CreateAutoPredictor or CreatePredictor operations
`create_what_if_analysis`	What-if analysis is a scenario modeling technique where you make a hypothetical change to a time series and compare the forecasts generated by these changes against the baseline, unchanged time series
`create_what_if_forecast`	A what-if forecast is a forecast that is created from a modified version of the baseline forecast
`create_what_if_forecast_export`	Exports a forecast created by the CreateWhatIfForecast operation to your Amazon Simple Storage Service (Amazon S3) bucket
`delete_dataset`	Deletes an Amazon Forecast dataset that was created using the CreateDataset operation
`delete_dataset_group`	Deletes a dataset group created using the CreateDatasetGroup operation
`delete_dataset_import_job`	Deletes a dataset import job created using the CreateDatasetImportJob operation
`delete_explainability`	Deletes an Explainability resource
`delete_explainability_export`	Deletes an Explainability export
`delete_forecast`	Deletes a forecast created using the CreateForecast operation
`delete_forecast_export_job`	Deletes a forecast export job created using the CreateForecastExportJob operation
`delete_monitor`	Deletes a monitor resource
`delete_predictor`	Deletes a predictor created using the DescribePredictor or CreatePredictor operations
`delete_predictor_backtest_export_job`	Deletes a predictor backtest export job
`delete_resource_tree`	Deletes an entire resource tree
`delete_what_if_analysis`	Deletes a what-if analysis created using the CreateWhatIfAnalysis operation
`delete_what_if_forecast`	Deletes a what-if forecast created using the CreateWhatIfForecast operation
`delete_what_if_forecast_export`	Deletes a what-if forecast export created using the CreateWhatIfForecastExport operation
`describe_auto_predictor`	Describes a predictor created using the CreateAutoPredictor operation
`describe_dataset`	Describes an Amazon Forecast dataset created using the CreateDataset operation
`describe_dataset_group`	Describes a dataset group created using the CreateDatasetGroup operation
`describe_dataset_import_job`	Describes a dataset import job created using the CreateDatasetImportJob operation
`describe_explainability`	Describes an Explainability resource created using the CreateExplainability operation
`describe_explainability_export`	Describes an Explainability export created using the CreateExplainabilityExport operation
`describe_forecast`	Describes a forecast created using the CreateForecast operation
`describe_forecast_export_job`	Describes a forecast export job created using the CreateForecastExportJob operation
`describe_monitor`	Describes a monitor resource
`describe_predictor`	This operation is only valid for legacy predictors created with CreatePredictor
`describe_predictor_backtest_export_job`	Describes a predictor backtest export job created using the CreatePredictorBacktestExportJob operation
`describe_what_if_analysis`	Describes the what-if analysis created using the CreateWhatIfAnalysis operation
`describe_what_if_forecast`	Describes the what-if forecast created using the CreateWhatIfForecast operation
`describe_what_if_forecast_export`	Describes the what-if forecast export created using the CreateWhatIfForecastExport operation
`get_accuracy_metrics`	Provides metrics on the accuracy of the models that were trained by the CreatePredictor operation
`list_dataset_groups`	Returns a list of dataset groups created using the CreateDatasetGroup operation
`list_dataset_import_jobs`	Returns a list of dataset import jobs created using the CreateDatasetImportJob operation
`list_datasets`	Returns a list of datasets created using the CreateDataset operation
`list_explainabilities`	Returns a list of Explainability resources created using the CreateExplainability operation
`list_explainability_exports`	Returns a list of Explainability exports created using the CreateExplainabilityExport operation
`list_forecast_export_jobs`	Returns a list of forecast export jobs created using the CreateForecastExportJob operation
`list_forecasts`	Returns a list of forecasts created using the CreateForecast operation
`list_monitor_evaluations`	Returns a list of the monitoring evaluation results and predictor events collected by the monitor resource during different windows of time
`list_monitors`	Returns a list of monitors created with the CreateMonitor operation and CreateAutoPredictor operation
`list_predictor_backtest_export_jobs`	Returns a list of predictor backtest export jobs created using the CreatePredictorBacktestExportJob operation
`list_predictors`	Returns a list of predictors created using the CreateAutoPredictor or CreatePredictor operations
`list_tags_for_resource`	Lists the tags for an Amazon Forecast resource
`list_what_if_analyses`	Returns a list of what-if analyses created using the CreateWhatIfAnalysis operation
`list_what_if_forecast_exports`	Returns a list of what-if forecast exports created using the CreateWhatIfForecastExport operation
`list_what_if_forecasts`	Returns a list of what-if forecasts created using the CreateWhatIfForecast operation
`resume_resource`	Resumes a stopped monitor resource
`stop_resource`	Stops a resource
`tag_resource`	Associates the specified tags to a resource with the specified resourceArn
`untag_resource`	Deletes the specified tags from a resource
`update_dataset_group`	Replaces the datasets in a dataset group with the specified datasets

Examples¶

svc <- forecastservice()
svc$create_auto_predictor(
  Foo = 123
)