forecastservice {paws.machine.learning} | 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 |
Optional credentials shorthand for the config parameter
|
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 |
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
## Not run:
svc <- forecastservice()
svc$create_auto_predictor(
Foo = 123
)
## End(Not run)