@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public interface AmazonForecast
Note: Do not directly implement this interface, new methods are added to it regularly. Extend from
AbstractAmazonForecast instead.
Provides APIs for creating and managing Amazon Forecast resources.
| Modifier and Type | Field and Description |
|---|---|
static String |
ENDPOINT_PREFIX
The region metadata service name for computing region endpoints.
|
| Modifier and Type | Method and Description |
|---|---|
CreateAutoPredictorResult |
createAutoPredictor(CreateAutoPredictorRequest createAutoPredictorRequest)
Creates an Amazon Forecast predictor.
|
CreateDatasetResult |
createDataset(CreateDatasetRequest createDatasetRequest)
Creates an Amazon Forecast dataset.
|
CreateDatasetGroupResult |
createDatasetGroup(CreateDatasetGroupRequest createDatasetGroupRequest)
Creates a dataset group, which holds a collection of related datasets.
|
CreateDatasetImportJobResult |
createDatasetImportJob(CreateDatasetImportJobRequest createDatasetImportJobRequest)
Imports your training data to an Amazon Forecast dataset.
|
CreateExplainabilityResult |
createExplainability(CreateExplainabilityRequest createExplainabilityRequest)
|
CreateExplainabilityExportResult |
createExplainabilityExport(CreateExplainabilityExportRequest createExplainabilityExportRequest)
Exports an Explainability resource created by the CreateExplainability operation.
|
CreateForecastResult |
createForecast(CreateForecastRequest createForecastRequest)
Creates a forecast for each item in the
TARGET_TIME_SERIES dataset that was used to train the
predictor. |
CreateForecastExportJobResult |
createForecastExportJob(CreateForecastExportJobRequest createForecastExportJobRequest)
Exports a forecast created by the CreateForecast operation to your Amazon Simple Storage Service (Amazon
S3) bucket.
|
CreateMonitorResult |
createMonitor(CreateMonitorRequest createMonitorRequest)
Creates a predictor monitor resource for an existing auto predictor.
|
CreatePredictorResult |
createPredictor(CreatePredictorRequest createPredictorRequest)
|
CreatePredictorBacktestExportJobResult |
createPredictorBacktestExportJob(CreatePredictorBacktestExportJobRequest createPredictorBacktestExportJobRequest)
Exports backtest forecasts and accuracy metrics generated by the CreateAutoPredictor or
CreatePredictor operations.
|
CreateWhatIfAnalysisResult |
createWhatIfAnalysis(CreateWhatIfAnalysisRequest createWhatIfAnalysisRequest)
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.
|
CreateWhatIfForecastResult |
createWhatIfForecast(CreateWhatIfForecastRequest createWhatIfForecastRequest)
A what-if forecast is a forecast that is created from a modified version of the baseline forecast.
|
CreateWhatIfForecastExportResult |
createWhatIfForecastExport(CreateWhatIfForecastExportRequest createWhatIfForecastExportRequest)
Exports a forecast created by the CreateWhatIfForecast operation to your Amazon Simple Storage Service
(Amazon S3) bucket.
|
DeleteDatasetResult |
deleteDataset(DeleteDatasetRequest deleteDatasetRequest)
Deletes an Amazon Forecast dataset that was created using the CreateDataset operation.
|
DeleteDatasetGroupResult |
deleteDatasetGroup(DeleteDatasetGroupRequest deleteDatasetGroupRequest)
Deletes a dataset group created using the CreateDatasetGroup
operation.
|
DeleteDatasetImportJobResult |
deleteDatasetImportJob(DeleteDatasetImportJobRequest deleteDatasetImportJobRequest)
Deletes a dataset import job created using the CreateDatasetImportJob
operation.
|
DeleteExplainabilityResult |
deleteExplainability(DeleteExplainabilityRequest deleteExplainabilityRequest)
Deletes an Explainability resource.
|
DeleteExplainabilityExportResult |
deleteExplainabilityExport(DeleteExplainabilityExportRequest deleteExplainabilityExportRequest)
Deletes an Explainability export.
|
DeleteForecastResult |
deleteForecast(DeleteForecastRequest deleteForecastRequest)
Deletes a forecast created using the CreateForecast operation.
|
DeleteForecastExportJobResult |
deleteForecastExportJob(DeleteForecastExportJobRequest deleteForecastExportJobRequest)
Deletes a forecast export job created using the CreateForecastExportJob operation.
|
DeleteMonitorResult |
deleteMonitor(DeleteMonitorRequest deleteMonitorRequest)
Deletes a monitor resource.
|
DeletePredictorResult |
deletePredictor(DeletePredictorRequest deletePredictorRequest)
Deletes a predictor created using the DescribePredictor or CreatePredictor operations.
|
DeletePredictorBacktestExportJobResult |
deletePredictorBacktestExportJob(DeletePredictorBacktestExportJobRequest deletePredictorBacktestExportJobRequest)
Deletes a predictor backtest export job.
|
DeleteResourceTreeResult |
deleteResourceTree(DeleteResourceTreeRequest deleteResourceTreeRequest)
Deletes an entire resource tree.
|
DeleteWhatIfAnalysisResult |
deleteWhatIfAnalysis(DeleteWhatIfAnalysisRequest deleteWhatIfAnalysisRequest)
Deletes a what-if analysis created using the CreateWhatIfAnalysis operation.
|
DeleteWhatIfForecastResult |
deleteWhatIfForecast(DeleteWhatIfForecastRequest deleteWhatIfForecastRequest)
Deletes a what-if forecast created using the CreateWhatIfForecast operation.
|
DeleteWhatIfForecastExportResult |
deleteWhatIfForecastExport(DeleteWhatIfForecastExportRequest deleteWhatIfForecastExportRequest)
Deletes a what-if forecast export created using the CreateWhatIfForecastExport operation.
|
DescribeAutoPredictorResult |
describeAutoPredictor(DescribeAutoPredictorRequest describeAutoPredictorRequest)
Describes a predictor created using the CreateAutoPredictor operation.
|
DescribeDatasetResult |
describeDataset(DescribeDatasetRequest describeDatasetRequest)
Describes an Amazon Forecast dataset created using the CreateDataset operation.
|
DescribeDatasetGroupResult |
describeDatasetGroup(DescribeDatasetGroupRequest describeDatasetGroupRequest)
Describes a dataset group created using the CreateDatasetGroup
operation.
|
DescribeDatasetImportJobResult |
describeDatasetImportJob(DescribeDatasetImportJobRequest describeDatasetImportJobRequest)
Describes a dataset import job created using the CreateDatasetImportJob
operation.
|
DescribeExplainabilityResult |
describeExplainability(DescribeExplainabilityRequest describeExplainabilityRequest)
Describes an Explainability resource created using the CreateExplainability operation.
|
DescribeExplainabilityExportResult |
describeExplainabilityExport(DescribeExplainabilityExportRequest describeExplainabilityExportRequest)
Describes an Explainability export created using the CreateExplainabilityExport operation.
|
DescribeForecastResult |
describeForecast(DescribeForecastRequest describeForecastRequest)
Describes a forecast created using the CreateForecast operation.
|
DescribeForecastExportJobResult |
describeForecastExportJob(DescribeForecastExportJobRequest describeForecastExportJobRequest)
Describes a forecast export job created using the CreateForecastExportJob operation.
|
DescribeMonitorResult |
describeMonitor(DescribeMonitorRequest describeMonitorRequest)
Describes a monitor resource.
|
DescribePredictorResult |
describePredictor(DescribePredictorRequest describePredictorRequest)
|
DescribePredictorBacktestExportJobResult |
describePredictorBacktestExportJob(DescribePredictorBacktestExportJobRequest describePredictorBacktestExportJobRequest)
Describes a predictor backtest export job created using the CreatePredictorBacktestExportJob operation.
|
DescribeWhatIfAnalysisResult |
describeWhatIfAnalysis(DescribeWhatIfAnalysisRequest describeWhatIfAnalysisRequest)
Describes the what-if analysis created using the CreateWhatIfAnalysis operation.
|
DescribeWhatIfForecastResult |
describeWhatIfForecast(DescribeWhatIfForecastRequest describeWhatIfForecastRequest)
Describes the what-if forecast created using the CreateWhatIfForecast operation.
|
DescribeWhatIfForecastExportResult |
describeWhatIfForecastExport(DescribeWhatIfForecastExportRequest describeWhatIfForecastExportRequest)
Describes the what-if forecast export created using the CreateWhatIfForecastExport operation.
|
GetAccuracyMetricsResult |
getAccuracyMetrics(GetAccuracyMetricsRequest getAccuracyMetricsRequest)
Provides metrics on the accuracy of the models that were trained by the CreatePredictor operation.
|
ResponseMetadata |
getCachedResponseMetadata(AmazonWebServiceRequest request)
Returns additional metadata for a previously executed successful request, typically used for debugging issues
where a service isn't acting as expected.
|
ListDatasetGroupsResult |
listDatasetGroups(ListDatasetGroupsRequest listDatasetGroupsRequest)
Returns a list of dataset groups created using the CreateDatasetGroup
operation.
|
ListDatasetImportJobsResult |
listDatasetImportJobs(ListDatasetImportJobsRequest listDatasetImportJobsRequest)
Returns a list of dataset import jobs created using the CreateDatasetImportJob
operation.
|
ListDatasetsResult |
listDatasets(ListDatasetsRequest listDatasetsRequest)
Returns a list of datasets created using the CreateDataset operation.
|
ListExplainabilitiesResult |
listExplainabilities(ListExplainabilitiesRequest listExplainabilitiesRequest)
Returns a list of Explainability resources created using the CreateExplainability operation.
|
ListExplainabilityExportsResult |
listExplainabilityExports(ListExplainabilityExportsRequest listExplainabilityExportsRequest)
Returns a list of Explainability exports created using the CreateExplainabilityExport operation.
|
ListForecastExportJobsResult |
listForecastExportJobs(ListForecastExportJobsRequest listForecastExportJobsRequest)
Returns a list of forecast export jobs created using the CreateForecastExportJob operation.
|
ListForecastsResult |
listForecasts(ListForecastsRequest listForecastsRequest)
Returns a list of forecasts created using the CreateForecast operation.
|
ListMonitorEvaluationsResult |
listMonitorEvaluations(ListMonitorEvaluationsRequest listMonitorEvaluationsRequest)
Returns a list of the monitoring evaluation results and predictor events collected by the monitor resource during
different windows of time.
|
ListMonitorsResult |
listMonitors(ListMonitorsRequest listMonitorsRequest)
Returns a list of monitors created with the CreateMonitor operation and CreateAutoPredictor
operation.
|
ListPredictorBacktestExportJobsResult |
listPredictorBacktestExportJobs(ListPredictorBacktestExportJobsRequest listPredictorBacktestExportJobsRequest)
Returns a list of predictor backtest export jobs created using the CreatePredictorBacktestExportJob
operation.
|
ListPredictorsResult |
listPredictors(ListPredictorsRequest listPredictorsRequest)
Returns a list of predictors created using the CreateAutoPredictor or CreatePredictor operations.
|
ListTagsForResourceResult |
listTagsForResource(ListTagsForResourceRequest listTagsForResourceRequest)
Lists the tags for an Amazon Forecast resource.
|
ListWhatIfAnalysesResult |
listWhatIfAnalyses(ListWhatIfAnalysesRequest listWhatIfAnalysesRequest)
Returns a list of what-if analyses created using the CreateWhatIfAnalysis operation.
|
ListWhatIfForecastExportsResult |
listWhatIfForecastExports(ListWhatIfForecastExportsRequest listWhatIfForecastExportsRequest)
Returns a list of what-if forecast exports created using the CreateWhatIfForecastExport operation.
|
ListWhatIfForecastsResult |
listWhatIfForecasts(ListWhatIfForecastsRequest listWhatIfForecastsRequest)
Returns a list of what-if forecasts created using the CreateWhatIfForecast operation.
|
ResumeResourceResult |
resumeResource(ResumeResourceRequest resumeResourceRequest)
Resumes a stopped monitor resource.
|
void |
shutdown()
Shuts down this client object, releasing any resources that might be held open.
|
StopResourceResult |
stopResource(StopResourceRequest stopResourceRequest)
Stops a resource.
|
TagResourceResult |
tagResource(TagResourceRequest tagResourceRequest)
Associates the specified tags to a resource with the specified
resourceArn. |
UntagResourceResult |
untagResource(UntagResourceRequest untagResourceRequest)
Deletes the specified tags from a resource.
|
UpdateDatasetGroupResult |
updateDatasetGroup(UpdateDatasetGroupRequest updateDatasetGroupRequest)
Replaces the datasets in a dataset group with the specified datasets.
|
static final String ENDPOINT_PREFIX
CreateAutoPredictorResult createAutoPredictor(CreateAutoPredictorRequest createAutoPredictorRequest)
Creates an Amazon Forecast predictor.
Amazon Forecast creates predictors with AutoPredictor, which involves applying the optimal combination of algorithms to each time series in your datasets. You can use CreateAutoPredictor to create new predictors or upgrade/retrain existing predictors.
Creating new predictors
The following parameters are required when creating a new predictor:
PredictorName - A unique name for the predictor.
DatasetGroupArn - The ARN of the dataset group used to train the predictor.
ForecastFrequency - The granularity of your forecasts (hourly, daily, weekly, etc).
ForecastHorizon - The number of time-steps that the model predicts. The forecast horizon is also
called the prediction length.
When creating a new predictor, do not specify a value for ReferencePredictorArn.
Upgrading and retraining predictors
The following parameters are required when retraining or upgrading a predictor:
PredictorName - A unique name for the predictor.
ReferencePredictorArn - The ARN of the predictor to retrain or upgrade.
When upgrading or retraining a predictor, only specify values for the ReferencePredictorArn and
PredictorName.
createAutoPredictorRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateDatasetResult createDataset(CreateDatasetRequest createDatasetRequest)
Creates an Amazon Forecast dataset. The information about the dataset that you provide helps Forecast understand how to consume the data for model training. This includes the following:
DataFrequency - How frequently your historical time-series data is collected.
Domain and DatasetType - Each dataset has an associated dataset
domain and a type within the domain. Amazon Forecast provides a list of predefined domains and types within each
domain. For each unique dataset domain and type within the domain, Amazon Forecast requires your data to include
a minimum set of predefined fields.
Schema - A schema specifies the fields in the dataset, including the field name and data
type.
After creating a dataset, you import your training data into it and add the dataset to a dataset group. You use the dataset group to create a predictor. For more information, see Importing datasets.
To get a list of all your datasets, use the ListDatasets operation.
For example Forecast datasets, see the Amazon Forecast Sample GitHub repository.
The Status of a dataset must be ACTIVE before you can import training data. Use the DescribeDataset operation to
get the status.
createDatasetRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateDatasetGroupResult createDatasetGroup(CreateDatasetGroupRequest createDatasetGroupRequest)
Creates a dataset group, which holds a collection of related datasets. You can add datasets to the dataset group when you create the dataset group, or later by using the UpdateDatasetGroup operation.
After creating a dataset group and adding datasets, you use the dataset group when you create a predictor. For more information, see Dataset groups.
To get a list of all your datasets groups, use the ListDatasetGroups operation.
The Status of a dataset group must be ACTIVE before you can use the dataset group to
create a predictor. To get the status, use the DescribeDatasetGroup
operation.
createDatasetGroupRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateDatasetImportJobResult createDatasetImportJob(CreateDatasetImportJobRequest createDatasetImportJobRequest)
Imports your training data to an Amazon Forecast dataset. You provide the location of your training data in an Amazon Simple Storage Service (Amazon S3) bucket and the Amazon Resource Name (ARN) of the dataset that you want to import the data to.
You must specify a DataSource object that includes an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data, as Amazon Forecast makes a copy of your data and processes it in an internal Amazon Web Services system. For more information, see Set up permissions.
The training data must be in CSV or Parquet format. The delimiter must be a comma (,).
You can specify the path to a specific file, the S3 bucket, or to a folder in the S3 bucket. For the latter two cases, Amazon Forecast imports all files up to the limit of 10,000 files.
Because dataset imports are not aggregated, your most recent dataset import is the one that is used when training a predictor or generating a forecast. Make sure that your most recent dataset import contains all of the data you want to model off of, and not just the new data collected since the previous import.
To get a list of all your dataset import jobs, filtered by specified criteria, use the ListDatasetImportJobs operation.
createDatasetImportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateExplainabilityResult createExplainability(CreateExplainabilityRequest createExplainabilityRequest)
Explainability is only available for Forecasts and Predictors generated from an AutoPredictor (CreateAutoPredictor)
Creates an Amazon Forecast Explainability.
Explainability helps you better understand how the attributes in your datasets impact forecast. Amazon Forecast uses a metric called Impact scores to quantify the relative impact of each attribute and determine whether they increase or decrease forecast values.
To enable Forecast Explainability, your predictor must include at least one of the following: related time series, item metadata, or additional datasets like Holidays and the Weather Index.
CreateExplainability accepts either a Predictor ARN or Forecast ARN. To receive aggregated Impact scores for all time series and time points in your datasets, provide a Predictor ARN. To receive Impact scores for specific time series and time points, provide a Forecast ARN.
CreateExplainability with a Predictor ARN
You can only have one Explainability resource per predictor. If you already enabled ExplainPredictor
in CreateAutoPredictor, that predictor already has an Explainability resource.
The following parameters are required when providing a Predictor ARN:
ExplainabilityName - A unique name for the Explainability.
ResourceArn - The Arn of the predictor.
TimePointGranularity - Must be set to “ALL”.
TimeSeriesGranularity - Must be set to “ALL”.
Do not specify a value for the following parameters:
DataSource - Only valid when TimeSeriesGranularity is “SPECIFIC”.
Schema - Only valid when TimeSeriesGranularity is “SPECIFIC”.
StartDateTime - Only valid when TimePointGranularity is “SPECIFIC”.
EndDateTime - Only valid when TimePointGranularity is “SPECIFIC”.
CreateExplainability with a Forecast ARN
You can specify a maximum of 50 time series and 500 time points.
The following parameters are required when providing a Predictor ARN:
ExplainabilityName - A unique name for the Explainability.
ResourceArn - The Arn of the forecast.
TimePointGranularity - Either “ALL” or “SPECIFIC”.
TimeSeriesGranularity - Either “ALL” or “SPECIFIC”.
If you set TimeSeriesGranularity to “SPECIFIC”, you must also provide the following:
DataSource - The S3 location of the CSV file specifying your time series.
Schema - The Schema defines the attributes and attribute types listed in the Data Source.
If you set TimePointGranularity to “SPECIFIC”, you must also provide the following:
StartDateTime - The first timestamp in the range of time points.
EndDateTime - The last timestamp in the range of time points.
createExplainabilityRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateExplainabilityExportResult createExplainabilityExport(CreateExplainabilityExportRequest createExplainabilityExportRequest)
Exports an Explainability resource created by the CreateExplainability operation. Exported files are exported to an Amazon Simple Storage Service (Amazon S3) bucket.
You must specify a DataDestination object that includes an Amazon S3 bucket and an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket. For more information, see aws-forecast-iam-roles.
The Status of the export job must be ACTIVE before you can access the export in your
Amazon S3 bucket. To get the status, use the DescribeExplainabilityExport operation.
createExplainabilityExportRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateForecastResult createForecast(CreateForecastRequest createForecastRequest)
Creates a forecast for each item in the TARGET_TIME_SERIES dataset that was used to train the
predictor. This is known as inference. To retrieve the forecast for a single item at low latency, use the
operation. To export the complete forecast into your Amazon Simple Storage Service (Amazon S3) bucket, use the
CreateForecastExportJob operation.
The range of the forecast is determined by the ForecastHorizon value, which you specify in the
CreatePredictor request. When you query a forecast, you can request a specific date range within the
forecast.
To get a list of all your forecasts, use the ListForecasts operation.
The forecasts generated by Amazon Forecast are in the same time zone as the dataset that was used to create the predictor.
For more information, see howitworks-forecast.
The Status of the forecast must be ACTIVE before you can query or export the forecast.
Use the DescribeForecast operation to get the status.
By default, a forecast includes predictions for every item (item_id) in the dataset group that was
used to train the predictor. However, you can use the TimeSeriesSelector object to generate a
forecast on a subset of time series. Forecast creation is skipped for any time series that you specify that are
not in the input dataset. The forecast export file will not contain these time series or their forecasted values.
createForecastRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateForecastExportJobResult createForecastExportJob(CreateForecastExportJobRequest createForecastExportJobRequest)
Exports a forecast created by the CreateForecast operation to your Amazon Simple Storage Service (Amazon S3) bucket. The forecast file name will match the following conventions:
<ForecastExportJobName>_<ExportTimestamp>_<PartNumber>
where the <ExportTimestamp> component is in Java SimpleDateFormat (yyyy-MM-ddTHH-mm-ssZ).
You must specify a DataDestination object that includes an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket. For more information, see aws-forecast-iam-roles.
For more information, see howitworks-forecast.
To get a list of all your forecast export jobs, use the ListForecastExportJobs operation.
The Status of the forecast export job must be ACTIVE before you can access the forecast
in your Amazon S3 bucket. To get the status, use the DescribeForecastExportJob operation.
createForecastExportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateMonitorResult createMonitor(CreateMonitorRequest createMonitorRequest)
Creates a predictor monitor resource for an existing auto predictor. Predictor monitoring allows you to see how your predictor's performance changes over time. For more information, see Predictor Monitoring.
createMonitorRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreatePredictorResult createPredictor(CreatePredictorRequest createPredictorRequest)
This operation creates a legacy predictor that does not include all the predictor functionalities provided by Amazon Forecast. To create a predictor that is compatible with all aspects of Forecast, use CreateAutoPredictor.
Creates an Amazon Forecast predictor.
In the request, provide a dataset group and either specify an algorithm or let Amazon Forecast choose an algorithm for you using AutoML. If you specify an algorithm, you also can override algorithm-specific hyperparameters.
Amazon Forecast uses the algorithm to train a predictor using the latest version of the datasets in the specified dataset group. You can then generate a forecast using the CreateForecast operation.
To see the evaluation metrics, use the GetAccuracyMetrics operation.
You can specify a featurization configuration to fill and aggregate the data fields in the
TARGET_TIME_SERIES dataset to improve model training. For more information, see
FeaturizationConfig.
For RELATED_TIME_SERIES datasets, CreatePredictor verifies that the DataFrequency
specified when the dataset was created matches the ForecastFrequency. TARGET_TIME_SERIES datasets
don't have this restriction. Amazon Forecast also verifies the delimiter and timestamp format. For more
information, see howitworks-datasets-groups.
By default, predictors are trained and evaluated at the 0.1 (P10), 0.5 (P50), and 0.9 (P90) quantiles. You can
choose custom forecast types to train and evaluate your predictor by setting the ForecastTypes.
AutoML
If you want Amazon Forecast to evaluate each algorithm and choose the one that minimizes the
objective function, set PerformAutoML to true. The
objective function is defined as the mean of the weighted losses over the forecast types. By
default, these are the p10, p50, and p90 quantile losses. For more information, see EvaluationResult.
When AutoML is enabled, the following properties are disallowed:
AlgorithmArn
HPOConfig
PerformHPO
TrainingParameters
To get a list of all of your predictors, use the ListPredictors operation.
Before you can use the predictor to create a forecast, the Status of the predictor must be
ACTIVE, signifying that training has completed. To get the status, use the DescribePredictor
operation.
createPredictorRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreatePredictorBacktestExportJobResult createPredictorBacktestExportJob(CreatePredictorBacktestExportJobRequest createPredictorBacktestExportJobRequest)
Exports backtest forecasts and accuracy metrics generated by the CreateAutoPredictor or CreatePredictor operations. Two folders containing CSV or Parquet files are exported to your specified S3 bucket.
The export file names will match the following conventions:
<ExportJobName>_<ExportTimestamp>_<PartNumber>.csv
The <ExportTimestamp> component is in Java SimpleDate format (yyyy-MM-ddTHH-mm-ssZ).
You must specify a DataDestination object that includes an Amazon S3 bucket and an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket. For more information, see aws-forecast-iam-roles.
The Status of the export job must be ACTIVE before you can access the export in your
Amazon S3 bucket. To get the status, use the DescribePredictorBacktestExportJob operation.
createPredictorBacktestExportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateWhatIfAnalysisResult createWhatIfAnalysis(CreateWhatIfAnalysisRequest createWhatIfAnalysisRequest)
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. It is important to remember that the purpose of a what-if analysis is to understand how a forecast can change given different modifications to the baseline time series.
For example, imagine you are a clothing retailer who is considering an end of season sale to clear space for new styles. After creating a baseline forecast, you can use a what-if analysis to investigate how different sales tactics might affect your goals.
You could create a scenario where everything is given a 25% markdown, and another where everything is given a fixed dollar markdown. You could create a scenario where the sale lasts for one week and another where the sale lasts for one month. With a what-if analysis, you can compare many different scenarios against each other.
Note that a what-if analysis is meant to display what the forecasting model has learned and how it will behave in the scenarios that you are evaluating. Do not blindly use the results of the what-if analysis to make business decisions. For instance, forecasts might not be accurate for novel scenarios where there is no reference available to determine whether a forecast is good.
The TimeSeriesSelector object defines the items that you want in the what-if analysis.
createWhatIfAnalysisRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateWhatIfForecastResult createWhatIfForecast(CreateWhatIfForecastRequest createWhatIfForecastRequest)
A what-if forecast is a forecast that is created from a modified version of the baseline forecast. Each what-if forecast incorporates either a replacement dataset or a set of transformations to the original dataset.
createWhatIfForecastRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.CreateWhatIfForecastExportResult createWhatIfForecastExport(CreateWhatIfForecastExportRequest createWhatIfForecastExportRequest)
Exports a forecast created by the CreateWhatIfForecast operation to your Amazon Simple Storage Service (Amazon S3) bucket. The forecast file name will match the following conventions:
≈<ForecastExportJobName>_<ExportTimestamp>_<PartNumber>
The <ExportTimestamp> component is in Java SimpleDateFormat (yyyy-MM-ddTHH-mm-ssZ).
You must specify a DataDestination object that includes an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket. For more information, see aws-forecast-iam-roles.
For more information, see howitworks-forecast.
To get a list of all your what-if forecast export jobs, use the ListWhatIfForecastExports operation.
The Status of the forecast export job must be ACTIVE before you can access the forecast
in your Amazon S3 bucket. To get the status, use the DescribeWhatIfForecastExport operation.
createWhatIfForecastExportRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceAlreadyExistsException - There is already a resource with this name. Try again with a different name.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.LimitExceededException - The limit on the number of resources per account has been exceeded.DeleteDatasetResult deleteDataset(DeleteDatasetRequest deleteDatasetRequest)
Deletes an Amazon Forecast dataset that was created using the CreateDataset operation. You can
only delete datasets that have a status of ACTIVE or CREATE_FAILED. To get the status
use the DescribeDataset
operation.
Forecast does not automatically update any dataset groups that contain the deleted dataset. In order to update the dataset group, use the UpdateDatasetGroup operation, omitting the deleted dataset's ARN.
deleteDatasetRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteDatasetGroupResult deleteDatasetGroup(DeleteDatasetGroupRequest deleteDatasetGroupRequest)
Deletes a dataset group created using the CreateDatasetGroup
operation. You can only delete dataset groups that have a status of ACTIVE,
CREATE_FAILED, or UPDATE_FAILED. To get the status, use the DescribeDatasetGroup
operation.
This operation deletes only the dataset group, not the datasets in the group.
deleteDatasetGroupRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteDatasetImportJobResult deleteDatasetImportJob(DeleteDatasetImportJobRequest deleteDatasetImportJobRequest)
Deletes a dataset import job created using the CreateDatasetImportJob
operation. You can delete only dataset import jobs that have a status of ACTIVE or
CREATE_FAILED. To get the status, use the DescribeDatasetImportJob operation.
deleteDatasetImportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteExplainabilityResult deleteExplainability(DeleteExplainabilityRequest deleteExplainabilityRequest)
Deletes an Explainability resource.
You can delete only predictor that have a status of ACTIVE or CREATE_FAILED. To get the
status, use the DescribeExplainability operation.
deleteExplainabilityRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteExplainabilityExportResult deleteExplainabilityExport(DeleteExplainabilityExportRequest deleteExplainabilityExportRequest)
Deletes an Explainability export.
deleteExplainabilityExportRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteForecastResult deleteForecast(DeleteForecastRequest deleteForecastRequest)
Deletes a forecast created using the CreateForecast operation. You can delete only forecasts that have a
status of ACTIVE or CREATE_FAILED. To get the status, use the DescribeForecast
operation.
You can't delete a forecast while it is being exported. After a forecast is deleted, you can no longer query the forecast.
deleteForecastRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteForecastExportJobResult deleteForecastExportJob(DeleteForecastExportJobRequest deleteForecastExportJobRequest)
Deletes a forecast export job created using the CreateForecastExportJob operation. You can delete only
export jobs that have a status of ACTIVE or CREATE_FAILED. To get the status, use the
DescribeForecastExportJob operation.
deleteForecastExportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteMonitorResult deleteMonitor(DeleteMonitorRequest deleteMonitorRequest)
Deletes a monitor resource. You can only delete a monitor resource with a status of ACTIVE,
ACTIVE_STOPPED, CREATE_FAILED, or CREATE_STOPPED.
deleteMonitorRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeletePredictorResult deletePredictor(DeletePredictorRequest deletePredictorRequest)
Deletes a predictor created using the DescribePredictor or CreatePredictor operations. You can
delete only predictor that have a status of ACTIVE or CREATE_FAILED. To get the status,
use the DescribePredictor operation.
deletePredictorRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeletePredictorBacktestExportJobResult deletePredictorBacktestExportJob(DeletePredictorBacktestExportJobRequest deletePredictorBacktestExportJobRequest)
Deletes a predictor backtest export job.
deletePredictorBacktestExportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteResourceTreeResult deleteResourceTree(DeleteResourceTreeRequest deleteResourceTreeRequest)
Deletes an entire resource tree. This operation will delete the parent resource and its child resources.
Child resources are resources that were created from another resource. For example, when a forecast is generated from a predictor, the forecast is the child resource and the predictor is the parent resource.
Amazon Forecast resources possess the following parent-child resource hierarchies:
Dataset: dataset import jobs
Dataset Group: predictors, predictor backtest export jobs, forecasts, forecast export jobs
Predictor: predictor backtest export jobs, forecasts, forecast export jobs
Forecast: forecast export jobs
DeleteResourceTree will only delete Amazon Forecast resources, and will not delete datasets or
exported files stored in Amazon S3.
deleteResourceTreeRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteWhatIfAnalysisResult deleteWhatIfAnalysis(DeleteWhatIfAnalysisRequest deleteWhatIfAnalysisRequest)
Deletes a what-if analysis created using the CreateWhatIfAnalysis operation. You can delete only what-if
analyses that have a status of ACTIVE or CREATE_FAILED. To get the status, use the
DescribeWhatIfAnalysis operation.
You can't delete a what-if analysis while any of its forecasts are being exported.
deleteWhatIfAnalysisRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteWhatIfForecastResult deleteWhatIfForecast(DeleteWhatIfForecastRequest deleteWhatIfForecastRequest)
Deletes a what-if forecast created using the CreateWhatIfForecast operation. You can delete only what-if
forecasts that have a status of ACTIVE or CREATE_FAILED. To get the status, use the
DescribeWhatIfForecast operation.
You can't delete a what-if forecast while it is being exported. After a what-if forecast is deleted, you can no longer query the what-if analysis.
deleteWhatIfForecastRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DeleteWhatIfForecastExportResult deleteWhatIfForecastExport(DeleteWhatIfForecastExportRequest deleteWhatIfForecastExportRequest)
Deletes a what-if forecast export created using the CreateWhatIfForecastExport operation. You can delete
only what-if forecast exports that have a status of ACTIVE or CREATE_FAILED. To get the
status, use the DescribeWhatIfForecastExport operation.
deleteWhatIfForecastExportRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.DescribeAutoPredictorResult describeAutoPredictor(DescribeAutoPredictorRequest describeAutoPredictorRequest)
Describes a predictor created using the CreateAutoPredictor operation.
describeAutoPredictorRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeDatasetResult describeDataset(DescribeDatasetRequest describeDatasetRequest)
Describes an Amazon Forecast dataset created using the CreateDataset operation.
In addition to listing the parameters specified in the CreateDataset request, this operation
includes the following dataset properties:
CreationTime
LastModificationTime
Status
describeDatasetRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeDatasetGroupResult describeDatasetGroup(DescribeDatasetGroupRequest describeDatasetGroupRequest)
Describes a dataset group created using the CreateDatasetGroup operation.
In addition to listing the parameters provided in the CreateDatasetGroup request, this operation
includes the following properties:
DatasetArns - The datasets belonging to the group.
CreationTime
LastModificationTime
Status
describeDatasetGroupRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeDatasetImportJobResult describeDatasetImportJob(DescribeDatasetImportJobRequest describeDatasetImportJobRequest)
Describes a dataset import job created using the CreateDatasetImportJob operation.
In addition to listing the parameters provided in the CreateDatasetImportJob request, this operation
includes the following properties:
CreationTime
LastModificationTime
DataSize
FieldStatistics
Status
Message - If an error occurred, information about the error.
describeDatasetImportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeExplainabilityResult describeExplainability(DescribeExplainabilityRequest describeExplainabilityRequest)
Describes an Explainability resource created using the CreateExplainability operation.
describeExplainabilityRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeExplainabilityExportResult describeExplainabilityExport(DescribeExplainabilityExportRequest describeExplainabilityExportRequest)
Describes an Explainability export created using the CreateExplainabilityExport operation.
describeExplainabilityExportRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeForecastResult describeForecast(DescribeForecastRequest describeForecastRequest)
Describes a forecast created using the CreateForecast operation.
In addition to listing the properties provided in the CreateForecast request, this operation lists
the following properties:
DatasetGroupArn - The dataset group that provided the training data.
CreationTime
LastModificationTime
Status
Message - If an error occurred, information about the error.
describeForecastRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeForecastExportJobResult describeForecastExportJob(DescribeForecastExportJobRequest describeForecastExportJobRequest)
Describes a forecast export job created using the CreateForecastExportJob operation.
In addition to listing the properties provided by the user in the CreateForecastExportJob request,
this operation lists the following properties:
CreationTime
LastModificationTime
Status
Message - If an error occurred, information about the error.
describeForecastExportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeMonitorResult describeMonitor(DescribeMonitorRequest describeMonitorRequest)
Describes a monitor resource. In addition to listing the properties provided in the CreateMonitor request, this operation lists the following properties:
Baseline
CreationTime
LastEvaluationTime
LastEvaluationState
LastModificationTime
Message
Status
describeMonitorRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribePredictorResult describePredictor(DescribePredictorRequest describePredictorRequest)
This operation is only valid for legacy predictors created with CreatePredictor. If you are not using a legacy predictor, use DescribeAutoPredictor.
Describes a predictor created using the CreatePredictor operation.
In addition to listing the properties provided in the CreatePredictor request, this operation lists
the following properties:
DatasetImportJobArns - The dataset import jobs used to import training data.
AutoMLAlgorithmArns - If AutoML is performed, the algorithms that were evaluated.
CreationTime
LastModificationTime
Status
Message - If an error occurred, information about the error.
describePredictorRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribePredictorBacktestExportJobResult describePredictorBacktestExportJob(DescribePredictorBacktestExportJobRequest describePredictorBacktestExportJobRequest)
Describes a predictor backtest export job created using the CreatePredictorBacktestExportJob operation.
In addition to listing the properties provided by the user in the CreatePredictorBacktestExportJob
request, this operation lists the following properties:
CreationTime
LastModificationTime
Status
Message (if an error occurred)
describePredictorBacktestExportJobRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeWhatIfAnalysisResult describeWhatIfAnalysis(DescribeWhatIfAnalysisRequest describeWhatIfAnalysisRequest)
Describes the what-if analysis created using the CreateWhatIfAnalysis operation.
In addition to listing the properties provided in the CreateWhatIfAnalysis request, this operation
lists the following properties:
CreationTime
LastModificationTime
Message - If an error occurred, information about the error.
Status
describeWhatIfAnalysisRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeWhatIfForecastResult describeWhatIfForecast(DescribeWhatIfForecastRequest describeWhatIfForecastRequest)
Describes the what-if forecast created using the CreateWhatIfForecast operation.
In addition to listing the properties provided in the CreateWhatIfForecast request, this operation
lists the following properties:
CreationTime
LastModificationTime
Message - If an error occurred, information about the error.
Status
describeWhatIfForecastRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.DescribeWhatIfForecastExportResult describeWhatIfForecastExport(DescribeWhatIfForecastExportRequest describeWhatIfForecastExportRequest)
Describes the what-if forecast export created using the CreateWhatIfForecastExport operation.
In addition to listing the properties provided in the CreateWhatIfForecastExport request, this
operation lists the following properties:
CreationTime
LastModificationTime
Message - If an error occurred, information about the error.
Status
describeWhatIfForecastExportRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.GetAccuracyMetricsResult getAccuracyMetrics(GetAccuracyMetricsRequest getAccuracyMetricsRequest)
Provides metrics on the accuracy of the models that were trained by the CreatePredictor operation. Use metrics to see how well the model performed and to decide whether to use the predictor to generate a forecast. For more information, see Predictor Metrics.
This operation generates metrics for each backtest window that was evaluated. The number of backtest windows (
NumberOfBacktestWindows) is specified using the EvaluationParameters object, which is
optionally included in the CreatePredictor request. If NumberOfBacktestWindows isn't
specified, the number defaults to one.
The parameters of the filling method determine which items contribute to the metrics. If you want
all items to contribute, specify zero. If you want only those items that have complete data in the
range being evaluated to contribute, specify nan. For more information, see
FeaturizationMethod.
Before you can get accuracy metrics, the Status of the predictor must be ACTIVE,
signifying that training has completed. To get the status, use the DescribePredictor operation.
getAccuracyMetricsRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.ListDatasetGroupsResult listDatasetGroups(ListDatasetGroupsRequest listDatasetGroupsRequest)
Returns a list of dataset groups created using the CreateDatasetGroup operation. For each dataset group, this operation returns a summary of its properties, including its Amazon Resource Name (ARN). You can retrieve the complete set of properties by using the dataset group ARN with the DescribeDatasetGroup operation.
listDatasetGroupsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.ListDatasetImportJobsResult listDatasetImportJobs(ListDatasetImportJobsRequest listDatasetImportJobsRequest)
Returns a list of dataset import jobs created using the CreateDatasetImportJob operation. For each import job, this operation returns a summary of its properties, including its Amazon Resource Name (ARN). You can retrieve the complete set of properties by using the ARN with the DescribeDatasetImportJob operation. You can filter the list by providing an array of Filter objects.
listDatasetImportJobsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListDatasetsResult listDatasets(ListDatasetsRequest listDatasetsRequest)
Returns a list of datasets created using the CreateDataset operation. For each dataset, a summary of its properties, including its Amazon Resource Name (ARN), is returned. To retrieve the complete set of properties, use the ARN with the DescribeDataset operation.
listDatasetsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.ListExplainabilitiesResult listExplainabilities(ListExplainabilitiesRequest listExplainabilitiesRequest)
Returns a list of Explainability resources created using the CreateExplainability operation. This operation returns a summary for each Explainability. You can filter the list using an array of Filter objects.
To retrieve the complete set of properties for a particular Explainability resource, use the ARN with the DescribeExplainability operation.
listExplainabilitiesRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListExplainabilityExportsResult listExplainabilityExports(ListExplainabilityExportsRequest listExplainabilityExportsRequest)
Returns a list of Explainability exports created using the CreateExplainabilityExport operation. This operation returns a summary for each Explainability export. You can filter the list using an array of Filter objects.
To retrieve the complete set of properties for a particular Explainability export, use the ARN with the DescribeExplainability operation.
listExplainabilityExportsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListForecastExportJobsResult listForecastExportJobs(ListForecastExportJobsRequest listForecastExportJobsRequest)
Returns a list of forecast export jobs created using the CreateForecastExportJob operation. For each forecast export job, this operation returns a summary of its properties, including its Amazon Resource Name (ARN). To retrieve the complete set of properties, use the ARN with the DescribeForecastExportJob operation. You can filter the list using an array of Filter objects.
listForecastExportJobsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListForecastsResult listForecasts(ListForecastsRequest listForecastsRequest)
Returns a list of forecasts created using the CreateForecast operation. For each forecast, this operation returns a summary of its properties, including its Amazon Resource Name (ARN). To retrieve the complete set of properties, specify the ARN with the DescribeForecast operation. You can filter the list using an array of Filter objects.
listForecastsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListMonitorEvaluationsResult listMonitorEvaluations(ListMonitorEvaluationsRequest listMonitorEvaluationsRequest)
Returns a list of the monitoring evaluation results and predictor events collected by the monitor resource during different windows of time.
For information about monitoring see predictor-monitoring. For more information about retrieving monitoring results see Viewing Monitoring Results.
listMonitorEvaluationsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ListMonitorsResult listMonitors(ListMonitorsRequest listMonitorsRequest)
Returns a list of monitors created with the CreateMonitor operation and CreateAutoPredictor operation. For each monitor resource, this operation returns of a summary of its properties, including its Amazon Resource Name (ARN). You can retrieve a complete set of properties of a monitor resource by specify the monitor's ARN in the DescribeMonitor operation.
listMonitorsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListPredictorBacktestExportJobsResult listPredictorBacktestExportJobs(ListPredictorBacktestExportJobsRequest listPredictorBacktestExportJobsRequest)
Returns a list of predictor backtest export jobs created using the CreatePredictorBacktestExportJob operation. This operation returns a summary for each backtest export job. You can filter the list using an array of Filter objects.
To retrieve the complete set of properties for a particular backtest export job, use the ARN with the DescribePredictorBacktestExportJob operation.
listPredictorBacktestExportJobsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListPredictorsResult listPredictors(ListPredictorsRequest listPredictorsRequest)
Returns a list of predictors created using the CreateAutoPredictor or CreatePredictor operations. For each predictor, this operation returns a summary of its properties, including its Amazon Resource Name (ARN).
You can retrieve the complete set of properties by using the ARN with the DescribeAutoPredictor and DescribePredictor operations. You can filter the list using an array of Filter objects.
listPredictorsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListTagsForResourceResult listTagsForResource(ListTagsForResourceRequest listTagsForResourceRequest)
Lists the tags for an Amazon Forecast resource.
listTagsForResourceRequest - ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListWhatIfAnalysesResult listWhatIfAnalyses(ListWhatIfAnalysesRequest listWhatIfAnalysesRequest)
Returns a list of what-if analyses created using the CreateWhatIfAnalysis operation. For each what-if analysis, this operation returns a summary of its properties, including its Amazon Resource Name (ARN). You can retrieve the complete set of properties by using the what-if analysis ARN with the DescribeWhatIfAnalysis operation.
listWhatIfAnalysesRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListWhatIfForecastExportsResult listWhatIfForecastExports(ListWhatIfForecastExportsRequest listWhatIfForecastExportsRequest)
Returns a list of what-if forecast exports created using the CreateWhatIfForecastExport operation. For each what-if forecast export, this operation returns a summary of its properties, including its Amazon Resource Name (ARN). You can retrieve the complete set of properties by using the what-if forecast export ARN with the DescribeWhatIfForecastExport operation.
listWhatIfForecastExportsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ListWhatIfForecastsResult listWhatIfForecasts(ListWhatIfForecastsRequest listWhatIfForecastsRequest)
Returns a list of what-if forecasts created using the CreateWhatIfForecast operation. For each what-if forecast, this operation returns a summary of its properties, including its Amazon Resource Name (ARN). You can retrieve the complete set of properties by using the what-if forecast ARN with the DescribeWhatIfForecast operation.
listWhatIfForecastsRequest - InvalidNextTokenException - The token is not valid. Tokens expire after 24 hours.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResumeResourceResult resumeResource(ResumeResourceRequest resumeResourceRequest)
Resumes a stopped monitor resource.
resumeResourceRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.LimitExceededException - The limit on the number of resources per account has been exceeded.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.StopResourceResult stopResource(StopResourceRequest stopResourceRequest)
Stops a resource.
The resource undergoes the following states: CREATE_STOPPING and CREATE_STOPPED. You
cannot resume a resource once it has been stopped.
This operation can be applied to the following resources (and their corresponding child resources):
Dataset Import Job
Predictor Job
Forecast Job
Forecast Export Job
Predictor Backtest Export Job
Explainability Job
Explainability Export Job
stopResourceRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.LimitExceededException - The limit on the number of resources per account has been exceeded.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.TagResourceResult tagResource(TagResourceRequest tagResourceRequest)
Associates the specified tags to a resource with the specified resourceArn. If existing tags on a
resource are not specified in the request parameters, they are not changed. When a resource is deleted, the tags
associated with that resource are also deleted.
tagResourceRequest - ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.LimitExceededException - The limit on the number of resources per account has been exceeded.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.UntagResourceResult untagResource(UntagResourceRequest untagResourceRequest)
Deletes the specified tags from a resource.
untagResourceRequest - ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.UpdateDatasetGroupResult updateDatasetGroup(UpdateDatasetGroupRequest updateDatasetGroupRequest)
Replaces the datasets in a dataset group with the specified datasets.
The Status of the dataset group must be ACTIVE before you can use the dataset group to
create a predictor. Use the DescribeDatasetGroup
operation to get the status.
updateDatasetGroupRequest - InvalidInputException - We can't process the request because it includes an invalid value or a value that exceeds the valid
range.ResourceNotFoundException - We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.ResourceInUseException - The specified resource is in use.void shutdown()
ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)
Response metadata is only cached for a limited period of time, so if you need to access this extra diagnostic information for an executed request, you should use this method to retrieve it as soon as possible after executing a request.
request - The originally executed request.Copyright © 2024. All rights reserved.