Expand description
Provides APIs for creating and managing Amazon Forecast resources.
If you’re using the service, you’re probably looking for ForecastClient and Forecast.
Structs§
- Categorical
Parameter Range Specifies a categorical hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
- Continuous
Parameter Range Specifies a continuous hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
- Create
Dataset Group Request - Create
Dataset Group Response - Create
Dataset Import JobRequest - Create
Dataset Import JobResponse - Create
Dataset Request - Create
Dataset Response - Create
Forecast Export JobRequest - Create
Forecast Export JobResponse - Create
Forecast Request - Create
Forecast Response - Create
Predictor Backtest Export JobRequest - Create
Predictor Backtest Export JobResponse - Create
Predictor Request - Create
Predictor Response - Data
Destination The destination for an export job. Provide an S3 path, an AWS Identity and Access Management (IAM) role that allows Amazon Forecast to access the location, and an AWS Key Management Service (KMS) key (optional).
- Data
Source The source of your training data, an AWS Identity and Access Management (IAM) role that allows Amazon Forecast to access the data and, optionally, an AWS Key Management Service (KMS) key. This object is submitted in the CreateDatasetImportJob request.
- Dataset
Group Summary Provides a summary of the dataset group properties used in the ListDatasetGroups operation. To get the complete set of properties, call the DescribeDatasetGroup operation, and provide the
DatasetGroupArn
.- Dataset
Import JobSummary Provides a summary of the dataset import job properties used in the ListDatasetImportJobs operation. To get the complete set of properties, call the DescribeDatasetImportJob operation, and provide the
DatasetImportJobArn
.- Dataset
Summary Provides a summary of the dataset properties used in the ListDatasets operation. To get the complete set of properties, call the DescribeDataset operation, and provide the
DatasetArn
.- Delete
Dataset Group Request - Delete
Dataset Import JobRequest - Delete
Dataset Request - Delete
Forecast Export JobRequest - Delete
Forecast Request - Delete
Predictor Backtest Export JobRequest - Delete
Predictor Request - Delete
Resource Tree Request - Describe
Dataset Group Request - Describe
Dataset Group Response - Describe
Dataset Import JobRequest - Describe
Dataset Import JobResponse - Describe
Dataset Request - Describe
Dataset Response - Describe
Forecast Export JobRequest - Describe
Forecast Export JobResponse - Describe
Forecast Request - Describe
Forecast Response - Describe
Predictor Backtest Export JobRequest - Describe
Predictor Backtest Export JobResponse - Describe
Predictor Request - Describe
Predictor Response - Encryption
Config An AWS Key Management Service (KMS) key and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key. You can specify this optional object in the CreateDataset and CreatePredictor requests.
- Error
Metric Provides detailed error metrics to evaluate the performance of a predictor. This object is part of the Metrics object.
- Evaluation
Parameters Parameters that define how to split a dataset into training data and testing data, and the number of iterations to perform. These parameters are specified in the predefined algorithms but you can override them in the CreatePredictor request.
- Evaluation
Result The results of evaluating an algorithm. Returned as part of the GetAccuracyMetrics response.
- Featurization
Provides featurization (transformation) information for a dataset field. This object is part of the FeaturizationConfig object.
For example:
{
"AttributeName": "demand",
FeaturizationPipeline [ {
"FeaturizationMethodName": "filling",
"FeaturizationMethodParameters": {"aggregation": "avg", "backfill": "nan"}
} ]
}
- Featurization
Config In a CreatePredictor operation, the specified algorithm trains a model using the specified dataset group. You can optionally tell the operation to modify data fields prior to training a model. These modifications are referred to as featurization.
You define featurization using the
FeaturizationConfig
object. You specify an array of transformations, one for each field that you want to featurize. You then include theFeaturizationConfig
object in yourCreatePredictor
request. Amazon Forecast applies the featurization to theTARGET_TIME_SERIES
andRELATED_TIME_SERIES
datasets before model training.You can create multiple featurization configurations. For example, you might call the
CreatePredictor
operation twice by specifying different featurization configurations.- Featurization
Method Provides information about the method that featurizes (transforms) a dataset field. The method is part of the
FeaturizationPipeline
of the Featurization object.The following is an example of how you specify a
FeaturizationMethod
object.{
"FeaturizationMethodName": "filling",
"FeaturizationMethodParameters": {"aggregation": "sum", "middlefill": "zero", "backfill": "zero"}
}
- Filter
Describes a filter for choosing a subset of objects. Each filter consists of a condition and a match statement. The condition is either
IS
orIS_NOT
, which specifies whether to include or exclude the objects that match the statement, respectively. The match statement consists of a key and a value.- Forecast
Client - A client for the Amazon Forecast Service API.
- Forecast
Export JobSummary Provides a summary of the forecast export job properties used in the ListForecastExportJobs operation. To get the complete set of properties, call the DescribeForecastExportJob operation, and provide the listed
ForecastExportJobArn
.- Forecast
Summary Provides a summary of the forecast properties used in the ListForecasts operation. To get the complete set of properties, call the DescribeForecast operation, and provide the
ForecastArn
that is listed in the summary.- GetAccuracy
Metrics Request - GetAccuracy
Metrics Response - Hyper
Parameter Tuning JobConfig Configuration information for a hyperparameter tuning job. You specify this object in the CreatePredictor request.
A hyperparameter is a parameter that governs the model training process. You set hyperparameters before training starts, unlike model parameters, which are determined during training. The values of the hyperparameters effect which values are chosen for the model parameters.
In a hyperparameter tuning job, Amazon Forecast chooses the set of hyperparameter values that optimize a specified metric. Forecast accomplishes this by running many training jobs over a range of hyperparameter values. The optimum set of values depends on the algorithm, the training data, and the specified metric objective.
- Input
Data Config The data used to train a predictor. The data includes a dataset group and any supplementary features. You specify this object in the CreatePredictor request.
- Integer
Parameter Range Specifies an integer hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
- List
Dataset Groups Request - List
Dataset Groups Response - List
Dataset Import Jobs Request - List
Dataset Import Jobs Response - List
Datasets Request - List
Datasets Response - List
Forecast Export Jobs Request - List
Forecast Export Jobs Response - List
Forecasts Request - List
Forecasts Response - List
Predictor Backtest Export Jobs Request - List
Predictor Backtest Export Jobs Response - List
Predictors Request - List
Predictors Response - List
Tags ForResource Request - List
Tags ForResource Response - Metrics
Provides metrics that are used to evaluate the performance of a predictor. This object is part of the WindowSummary object.
- Parameter
Ranges Specifies the categorical, continuous, and integer hyperparameters, and their ranges of tunable values. The range of tunable values determines which values that a hyperparameter tuning job can choose for the specified hyperparameter. This object is part of the HyperParameterTuningJobConfig object.
- Predictor
Backtest Export JobSummary Provides a summary of the predictor backtest export job properties used in the ListPredictorBacktestExportJobs operation. To get a complete set of properties, call the DescribePredictorBacktestExportJob operation, and provide the listed
PredictorBacktestExportJobArn
.- Predictor
Execution The algorithm used to perform a backtest and the status of those tests.
- Predictor
Execution Details Contains details on the backtests performed to evaluate the accuracy of the predictor. The tests are returned in descending order of accuracy, with the most accurate backtest appearing first. You specify the number of backtests to perform when you call the operation.
- Predictor
Summary Provides a summary of the predictor properties that are used in the ListPredictors operation. To get the complete set of properties, call the DescribePredictor operation, and provide the listed
PredictorArn
.- S3Config
The path to the file(s) in an Amazon Simple Storage Service (Amazon S3) bucket, and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the file(s). Optionally, includes an AWS Key Management Service (KMS) key. This object is part of the DataSource object that is submitted in the CreateDatasetImportJob request, and part of the DataDestination object.
- Schema
Defines the fields of a dataset. You specify this object in the CreateDataset request.
- Schema
Attribute An attribute of a schema, which defines a dataset field. A schema attribute is required for every field in a dataset. The Schema object contains an array of
SchemaAttribute
objects.- Statistics
Provides statistics for each data field imported into to an Amazon Forecast dataset with the CreateDatasetImportJob operation.
- Stop
Resource Request - Supplementary
Feature Describes a supplementary feature of a dataset group. This object is part of the InputDataConfig object. Forecast supports the Weather Index and Holidays built-in featurizations.
Weather Index
The Amazon Forecast Weather Index is a built-in featurization that incorporates historical and projected weather information into your model. The Weather Index supplements your datasets with over two years of historical weather data and up to 14 days of projected weather data. For more information, see Amazon Forecast Weather Index.
Holidays
Holidays is a built-in featurization that incorporates a feature-engineered dataset of national holiday information into your model. It provides native support for the holiday calendars of 66 countries. To view the holiday calendars, refer to the Jollyday library. For more information, see Holidays Featurization.
- Tag
The optional metadata that you apply to a resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.
The following basic restrictions apply to tags:
-
Maximum number of tags per resource - 50.
-
For each resource, each tag key must be unique, and each tag key can have only one value.
-
Maximum key length - 128 Unicode characters in UTF-8.
-
Maximum value length - 256 Unicode characters in UTF-8.
-
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
-
Tag keys and values are case sensitive.
-
Do not use
aws:
,AWS:
, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value hasaws
as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix ofaws
do not count against your tags per resource limit.
-
- TagResource
Request - TagResource
Response - Test
Window Summary The status, start time, and end time of a backtest, as well as a failure reason if applicable.
- Untag
Resource Request - Untag
Resource Response - Update
Dataset Group Request - Update
Dataset Group Response - Weighted
Quantile Loss The weighted loss value for a quantile. This object is part of the Metrics object.
- Window
Summary The metrics for a time range within the evaluation portion of a dataset. This object is part of the EvaluationResult object.
The
TestWindowStart
andTestWindowEnd
parameters are determined by theBackTestWindowOffset
parameter of the EvaluationParameters object.
Enums§
- Create
Dataset Error - Errors returned by CreateDataset
- Create
Dataset Group Error - Errors returned by CreateDatasetGroup
- Create
Dataset Import JobError - Errors returned by CreateDatasetImportJob
- Create
Forecast Error - Errors returned by CreateForecast
- Create
Forecast Export JobError - Errors returned by CreateForecastExportJob
- Create
Predictor Backtest Export JobError - Errors returned by CreatePredictorBacktestExportJob
- Create
Predictor Error - Errors returned by CreatePredictor
- Delete
Dataset Error - Errors returned by DeleteDataset
- Delete
Dataset Group Error - Errors returned by DeleteDatasetGroup
- Delete
Dataset Import JobError - Errors returned by DeleteDatasetImportJob
- Delete
Forecast Error - Errors returned by DeleteForecast
- Delete
Forecast Export JobError - Errors returned by DeleteForecastExportJob
- Delete
Predictor Backtest Export JobError - Errors returned by DeletePredictorBacktestExportJob
- Delete
Predictor Error - Errors returned by DeletePredictor
- Delete
Resource Tree Error - Errors returned by DeleteResourceTree
- Describe
Dataset Error - Errors returned by DescribeDataset
- Describe
Dataset Group Error - Errors returned by DescribeDatasetGroup
- Describe
Dataset Import JobError - Errors returned by DescribeDatasetImportJob
- Describe
Forecast Error - Errors returned by DescribeForecast
- Describe
Forecast Export JobError - Errors returned by DescribeForecastExportJob
- Describe
Predictor Backtest Export JobError - Errors returned by DescribePredictorBacktestExportJob
- Describe
Predictor Error - Errors returned by DescribePredictor
- GetAccuracy
Metrics Error - Errors returned by GetAccuracyMetrics
- List
Dataset Groups Error - Errors returned by ListDatasetGroups
- List
Dataset Import Jobs Error - Errors returned by ListDatasetImportJobs
- List
Datasets Error - Errors returned by ListDatasets
- List
Forecast Export Jobs Error - Errors returned by ListForecastExportJobs
- List
Forecasts Error - Errors returned by ListForecasts
- List
Predictor Backtest Export Jobs Error - Errors returned by ListPredictorBacktestExportJobs
- List
Predictors Error - Errors returned by ListPredictors
- List
Tags ForResource Error - Errors returned by ListTagsForResource
- Stop
Resource Error - Errors returned by StopResource
- TagResource
Error - Errors returned by TagResource
- Untag
Resource Error - Errors returned by UntagResource
- Update
Dataset Group Error - Errors returned by UpdateDatasetGroup
Traits§
- Forecast
- Trait representing the capabilities of the Amazon Forecast Service API. Amazon Forecast Service clients implement this trait.