Crate rusoto_forecast

Provides APIs for creating and managing Amazon Forecast resources.

If you're using the service, you're probably looking for ForecastClient and Forecast.

Structs

CategoricalParameterRange	Specifies a categorical hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
ContinuousParameterRange	Specifies a continuous hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
CreateDatasetGroupRequest
CreateDatasetGroupResponse
CreateDatasetImportJobRequest
CreateDatasetImportJobResponse
CreateDatasetRequest
CreateDatasetResponse
CreateForecastExportJobRequest
CreateForecastExportJobResponse
CreateForecastRequest
CreateForecastResponse
CreatePredictorRequest
CreatePredictorResponse
DataDestination	The destination for an exported forecast, an AWS Identity and Access Management (IAM) role that allows Amazon Forecast to access the location and, optionally, an AWS Key Management Service (KMS) key. This object is submitted in the CreateForecastExportJob request.
DataSource	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.
DatasetGroupSummary	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.
DatasetImportJobSummary	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.
DatasetSummary	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.
DeleteDatasetGroupRequest
DeleteDatasetImportJobRequest
DeleteDatasetRequest
DeleteForecastExportJobRequest
DeleteForecastRequest
DeletePredictorRequest
DescribeDatasetGroupRequest
DescribeDatasetGroupResponse
DescribeDatasetImportJobRequest
DescribeDatasetImportJobResponse
DescribeDatasetRequest
DescribeDatasetResponse
DescribeForecastExportJobRequest
DescribeForecastExportJobResponse
DescribeForecastRequest
DescribeForecastResponse
DescribePredictorRequest
DescribePredictorResponse
EncryptionConfig	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.
EvaluationParameters	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.
EvaluationResult	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"} } ] }
FeaturizationConfig	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 the FeaturizationConfig object in your CreatePredictor request. Amazon Forecast applies the featurization to the TARGET_TIME_SERIES and RELATED_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.
FeaturizationMethod	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 or IS_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.
ForecastClient	A client for the Amazon Forecast Service API.
ForecastExportJobSummary	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.
ForecastSummary	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.
GetAccuracyMetricsRequest
GetAccuracyMetricsResponse
HyperParameterTuningJobConfig	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.
InputDataConfig	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.
IntegerParameterRange	Specifies an integer hyperparameter and it's range of tunable values. This object is part of the ParameterRanges object.
ListDatasetGroupsRequest
ListDatasetGroupsResponse
ListDatasetImportJobsRequest
ListDatasetImportJobsResponse
ListDatasetsRequest
ListDatasetsResponse
ListForecastExportJobsRequest
ListForecastExportJobsResponse
ListForecastsRequest
ListForecastsResponse
ListPredictorsRequest
ListPredictorsResponse
ListTagsForResourceRequest
ListTagsForResourceResponse
Metrics	Provides metrics that are used to evaluate the performance of a predictor. This object is part of the WindowSummary object.
ParameterRanges	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.
PredictorExecution	The algorithm used to perform a backtest and the status of those tests.
PredictorExecutionDetails	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.
PredictorSummary	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 that is submitted in the CreateForecastExportJob request.
Schema	Defines the fields of a dataset. You specify this object in the CreateDataset request.
SchemaAttribute	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.
SupplementaryFeature	Describes a supplementary feature of a dataset group. This object is part of the InputDataConfig object. The only supported feature is a holiday calendar. If you use the calendar, all data in the datasets should belong to the same country as the calendar. For the holiday calendar data, see the Jollyday web site. India and Korea's holidays are not included in the Jollyday library, but both are supported by Amazon Forecast. Their holidays are: "IN" - INDIA JANUARY 26 - REPUBLIC DAY AUGUST 15 - INDEPENDENCE DAY OCTOBER 2 GANDHI'S BIRTHDAY "KR" - KOREA JANUARY 1 - NEW YEAR MARCH 1 - INDEPENDENCE MOVEMENT DAY MAY 5 - CHILDREN'S DAY JUNE 6 - MEMORIAL DAY AUGUST 15 - LIBERATION DAY OCTOBER 3 - NATIONAL FOUNDATION DAY OCTOBER 9 - HANGEUL DAY DECEMBER 25 - CHRISTMAS DAY
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 has aws 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 of aws do not count against your tags per resource limit.
TagResourceRequest
TagResourceResponse
TestWindowSummary	The status, start time, and end time of a backtest, as well as a failure reason if applicable.
UntagResourceRequest
UntagResourceResponse
UpdateDatasetGroupRequest
UpdateDatasetGroupResponse
WeightedQuantileLoss	The weighted loss value for a quantile. This object is part of the Metrics object.
WindowSummary	The metrics for a time range within the evaluation portion of a dataset. This object is part of the EvaluationResult object. The TestWindowStart and TestWindowEnd parameters are determined by the BackTestWindowOffset parameter of the EvaluationParameters object.

Enums

CreateDatasetError	Errors returned by CreateDataset
CreateDatasetGroupError	Errors returned by CreateDatasetGroup
CreateDatasetImportJobError	Errors returned by CreateDatasetImportJob
CreateForecastError	Errors returned by CreateForecast
CreateForecastExportJobError	Errors returned by CreateForecastExportJob
CreatePredictorError	Errors returned by CreatePredictor
DeleteDatasetError	Errors returned by DeleteDataset
DeleteDatasetGroupError	Errors returned by DeleteDatasetGroup
DeleteDatasetImportJobError	Errors returned by DeleteDatasetImportJob
DeleteForecastError	Errors returned by DeleteForecast
DeleteForecastExportJobError	Errors returned by DeleteForecastExportJob
DeletePredictorError	Errors returned by DeletePredictor
DescribeDatasetError	Errors returned by DescribeDataset
DescribeDatasetGroupError	Errors returned by DescribeDatasetGroup
DescribeDatasetImportJobError	Errors returned by DescribeDatasetImportJob
DescribeForecastError	Errors returned by DescribeForecast
DescribeForecastExportJobError	Errors returned by DescribeForecastExportJob
DescribePredictorError	Errors returned by DescribePredictor
GetAccuracyMetricsError	Errors returned by GetAccuracyMetrics
ListDatasetGroupsError	Errors returned by ListDatasetGroups
ListDatasetImportJobsError	Errors returned by ListDatasetImportJobs
ListDatasetsError	Errors returned by ListDatasets
ListForecastExportJobsError	Errors returned by ListForecastExportJobs
ListForecastsError	Errors returned by ListForecasts
ListPredictorsError	Errors returned by ListPredictors
ListTagsForResourceError	Errors returned by ListTagsForResource
TagResourceError	Errors returned by TagResource
UntagResourceError	Errors returned by UntagResource
UpdateDatasetGroupError	Errors returned by UpdateDatasetGroup

Traits

Forecast

Trait representing the capabilities of the Amazon Forecast Service API. Amazon Forecast Service clients implement this trait.