Client

forecastservice

R Documentation

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

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"
  ),
  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; 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¶

## Not run: 
svc <- forecastservice()
svc$create_auto_predictor(
  Foo = 123
)

## End(Not run)