forecastservice: Amazon Forecast Service

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

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
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)

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