If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

The number of items to return in the response.

If the response is truncated, Amazon Forecast returns this token. To retrieve the next set of results, use the token in the next request.

An array of objects that summarize each dataset group's properties.

The response's http status code.

The format of timestamps in the dataset. The format that you specify depends on the DataFrequency specified when the dataset was created. The following formats are supported

• "yyyy-MM-dd"

  For the following data frequencies: Y, M, W, and D

• "yyyy-MM-dd HH:mm:ss"

  For the following data frequencies: H, 30min, 15min, and 1min; and optionally, for: Y, M, W, and D

If the format isn't specified, Amazon Forecast expects the format to be "yyyy-MM-dd HH:mm:ss".

Automatically derive time zone information from the geolocation attribute. This option is ideal for datasets that contain timestamps in multiple time zones and those timestamps are expressed in local time.

The format of the geolocation attribute. The geolocation attribute can be formatted in one of two ways:

• LAT_LONG - the latitude and longitude in decimal format (Example: 47.61_-122.33).
• CC_POSTALCODE (US Only) - the country code (US), followed by the 5-digit ZIP code (Example: US_98121).

A single time zone for every item in your dataset. This option is ideal for datasets with all timestamps within a single time zone, or if all timestamps are normalized to a single time zone.

Refer to the Joda-Time API for a complete list of valid time zone names.

The optional metadata that you apply to the dataset import job 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.

The name for the dataset import job. We recommend including the current timestamp in the name, for example, 20190721DatasetImport. This can help you avoid getting a ResourceAlreadyExistsException exception.

The Amazon Resource Name (ARN) of the Amazon Forecast dataset that you want to import data to.

The location of the training data to import and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data. The training data must be stored in an Amazon S3 bucket.

If encryption is used, DataSource must include an AWS Key Management Service (KMS) key and the IAM role must allow Amazon Forecast permission to access the key. The KMS key and IAM role must match those specified in the EncryptionConfig parameter of the CreateDataset operation.

The Amazon Resource Name (ARN) of the dataset import job.

The response's http status code.

The Amazon Resource Name (ARN) of the dataset.

When the dataset was created.

The status of the dataset. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
• UPDATE_PENDING, UPDATE_IN_PROGRESS, UPDATE_FAILED

The UPDATE states apply while data is imported to the dataset from a call to the CreateDatasetImportJob operation and reflect the status of the dataset import job. For example, when the import job status is CREATE_IN_PROGRESS, the status of the dataset is UPDATE_IN_PROGRESS.

The Status of the dataset must be ACTIVE before you can import training data.

The frequency of data collection.

Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, "M" indicates every month and "30min" indicates every 30 minutes.

The Amazon Resource Name (ARN) of the dataset.

The domain associated with the dataset.

An array of SchemaAttribute objects that specify the dataset fields. Each SchemaAttribute specifies the name and data type of a field.

The dataset type.

The name of the dataset.

The AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

When you create a dataset, LastModificationTime is the same as CreationTime. While data is being imported to the dataset, LastModificationTime is the current time of the DescribeDataset call. After a CreateDatasetImportJob operation has finished, LastModificationTime is when the import job completed or failed.

The response's http status code.

An array of filters. For each filter, you provide a condition and a match statement. The condition is either IS or IS_NOT, which specifies whether to include or exclude the forecasts that match the statement from the list, respectively. The match statement consists of a key and a value.

Filter properties

• Condition - The condition to apply. Valid values are IS and IS_NOT. To include the forecasts that match the statement, specify IS. To exclude matching forecasts, specify IS_NOT.
• Key - The name of the parameter to filter on. Valid values are DatasetGroupArn, PredictorArn, and Status.
• Value - The value to match.

For example, to list all forecasts whose status is not ACTIVE, you would specify:

"Filters": [ { "Condition": "IS_NOT", "Key": "Status", "Value": "ACTIVE" } ]

If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

The number of items to return in the response.

An array of objects that summarize each forecast's properties.

If the response is truncated, Amazon Forecast returns this token. To retrieve the next set of results, use the token in the next request.

The response's http status code.

The Amazon Resource Name (ARN) that identifies the resource for which to list the tags. Currently, the supported resources are Forecast dataset groups, datasets, dataset import jobs, predictors, forecasts, and forecast export jobs.

The tags for the resource.

The response's http status code.

The Amazon Resource Name (ARN) that identifies the resource to stop. The supported ARNs are DatasetImportJobArn, PredictorArn, PredictorBacktestExportJobArn, ForecastArn, and ForecastExportJobArn.

The Amazon Resource Name (ARN) of the dataset import job.

When the dataset import job was created.

The status of the dataset import job. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
• CREATE_STOPPING, CREATE_STOPPED

The name of the dataset import job.

The Amazon Resource Name (ARN) of the dataset that the training data was imported to.

The format of timestamps in the dataset. The format that you specify depends on the DataFrequency specified when the dataset was created. The following formats are supported

• "yyyy-MM-dd"

  For the following data frequencies: Y, M, W, and D

• "yyyy-MM-dd HH:mm:ss"

  For the following data frequencies: H, 30min, 15min, and 1min; and optionally, for: Y, M, W, and D

The size of the dataset in gigabytes (GB) after the import job has finished.

The estimated time remaining in minutes for the dataset import job to complete.

Statistical information about each field in the input data.

The location of the training data to import and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data.

If encryption is used, DataSource includes an AWS Key Management Service (KMS) key.

The ARN of the dataset import job.

Whether TimeZone is automatically derived from the geolocation attribute.

If an error occurred, an informational message about the error.

The format of the geolocation attribute. Valid Values:"LAT_LONG" and "CC_POSTALCODE".

The single time zone applied to every item in the dataset

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

The response's http status code.

The Amazon Resource Name (ARN) of the forecast export job.

When the forecast export job was created.

The status of the forecast export job. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• CREATE_STOPPING, CREATE_STOPPED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

The Status of the forecast export job must be ACTIVE before you can access the forecast in your S3 bucket.

The path to the Amazon Simple Storage Service (Amazon S3) bucket where the forecast is exported.

The ARN of the forecast export job.

The Amazon Resource Name (ARN) of the exported forecast.

The name of the forecast export job.

If an error occurred, an informational message about the error.

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

The response's http status code.

The Amazon Resource Name (ARN) of the predictor that you want information about.

When the model training task was created.

The number of time-steps of the forecast. The forecast horizon is also called the prediction length.

The status of the predictor. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
• CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

Whether the predictor is set to perform AutoML.

When PerformAutoML is specified, the ARN of the chosen algorithm.

The default training parameters or overrides selected during model training. When running AutoML or choosing HPO with CNN-QR or DeepAR+, the optimized values for the chosen hyperparameters are returned. For more information, see aws-forecast-choosing-recipes.

The Amazon Resource Name (ARN) of the algorithm used for model training.

The hyperparameter override values for the algorithm.

The ARN of the predictor.

The accuracy metric used to optimize the predictor.

Details on the the status and results of the backtests performed to evaluate the accuracy of the predictor. You specify the number of backtests to perform when you call the operation.

An array of the ARNs of the dataset import jobs used to import training data for the predictor.

The estimated time remaining in minutes for the predictor training job to complete.

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.

Describes the dataset group that contains the data to use to train the predictor.

The name of the predictor.

The featurization configuration.

An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]

If an error occurred, an informational message about the error.

Whether the predictor is set to perform hyperparameter optimization (HPO).

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

The response's http status code.

The Amazon Resource Name (ARN) of the dataset to delete.

The Amazon Resource Name (ARN) of the forecast.

When the forecast creation task was created.

The status of the forecast. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• CREATE_STOPPING, CREATE_STOPPED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

The Status of the forecast must be ACTIVE before you can query or export the forecast.

The ARN of the predictor used to generate the forecast.

The forecast ARN as specified in the request.

The estimated time remaining in minutes for the forecast job to complete.

The name of the forecast.

The quantiles at which probabilistic forecasts were generated.

The ARN of the dataset group that provided the data used to train the predictor.

If an error occurred, an informational message about the error.

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

The response's http status code.

The frequency of data collection. This parameter is required for RELATED_TIME_SERIES datasets.

Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, "D" indicates every day and "15min" indicates every 15 minutes.

An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

The optional metadata that you apply to the dataset 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.

A name for the dataset.

The domain associated with the dataset. When you add a dataset to a dataset group, this value and the value specified for the Domain parameter of the CreateDatasetGroup operation must match.

The Domain and DatasetType that you choose determine the fields that must be present in the training data that you import to the dataset. For example, if you choose the RETAIL domain and TARGET_TIME_SERIES as the DatasetType, Amazon Forecast requires item_id, timestamp, and demand fields to be present in your data. For more information, see howitworks-datasets-groups.

The dataset type. Valid values depend on the chosen Domain.

The schema for the dataset. The schema attributes and their order must match the fields in your data. The dataset Domain and DatasetType that you choose determine the minimum required fields in your training data. For information about the required fields for a specific dataset domain and type, see howitworks-domains-ds-types.

The Amazon Resource Name (ARN) of the dataset.

The response's http status code.

The Amazon Resource Name (ARN) of the forecast export job to delete.

The Amazon Resource Name (ARN) of the predictor to delete.

An array of filters. For each filter, you provide a condition and a match statement. The condition is either IS or IS_NOT, which specifies whether to include or exclude the datasets that match the statement from the list, respectively. The match statement consists of a key and a value.

Filter properties

• Condition - The condition to apply. Valid values are IS and IS_NOT. To include the datasets that match the statement, specify IS. To exclude matching datasets, specify IS_NOT.
• Key - The name of the parameter to filter on. Valid values are DatasetArn and Status.
• Value - The value to match.

For example, to list all dataset import jobs whose status is ACTIVE, you specify the following filter:

"Filters": [ { "Condition": "IS", "Key": "Status", "Value": "ACTIVE" } ]

If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

The number of items to return in the response.

An array of objects that summarize each dataset import job's properties.

If the response is truncated, Amazon Forecast returns this token. To retrieve the next set of results, use the token in the next request.

The response's http status code.

The Amazon Resource Name (ARN) of the dataset import job to delete.

The Amazon Resource Name (ARN) of the predictor to get metrics for.

An array of results from evaluating the predictor.

The accuracy metric used to optimize the predictor.

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

The AutoML strategy used to train the predictor. Unless LatencyOptimized is specified, the AutoML strategy optimizes predictor accuracy.

This parameter is only valid for predictors trained using AutoML.

The response's http status code.

The Amazon Resource Name (ARN) of the dataset group to delete.

The ARN of the dataset group.

An array of the Amazon Resource Names (ARNs) of the datasets to add to the dataset group.

The response's http status code.

The optional metadata that you apply to the forecast export job 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.

The name for the forecast export job.

The Amazon Resource Name (ARN) of the forecast that you want to export.

The location where you want to save the forecast and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the location. The forecast must be exported to an Amazon S3 bucket.

If encryption is used, Destination must include an AWS Key Management Service (KMS) key. The IAM role must allow Amazon Forecast permission to access the key.

The Amazon Resource Name (ARN) of the export job.

The response's http status code.

Whether to perform AutoML. When Amazon Forecast performs AutoML, it evaluates the algorithms it provides and chooses the best algorithm and configuration for your training dataset.

The default value is false. In this case, you are required to specify an algorithm.

Set PerformAutoML to true to have Amazon Forecast perform AutoML. This is a good option if you aren't sure which algorithm is suitable for your training data. In this case, PerformHPO must be false.

The hyperparameters to override for model training. The hyperparameters that you can override are listed in the individual algorithms. For the list of supported algorithms, see aws-forecast-choosing-recipes.

The Amazon Resource Name (ARN) of the algorithm to use for model training. Required if PerformAutoML is not set to true.

Supported algorithms:

• arn:aws:forecast:::algorithm/ARIMA

• arn:aws:forecast:::algorithm/CNN-QR

• arn:aws:forecast:::algorithm/Deep_AR_Plus

• arn:aws:forecast:::algorithm/ETS

• arn:aws:forecast:::algorithm/NPTS

• arn:aws:forecast:::algorithm/Prophet

Provides hyperparameter override values for the algorithm. If you don't provide this parameter, Amazon Forecast uses default values. The individual algorithms specify which hyperparameters support hyperparameter optimization (HPO). For more information, see aws-forecast-choosing-recipes.

If you included the HPOConfig object, you must set PerformHPO to true.

The accuracy metric used to optimize the predictor.

The LatencyOptimized AutoML override strategy is only available in private beta. Contact AWS Support or your account manager to learn more about access privileges.

Used to overide the default AutoML strategy, which is to optimize predictor accuracy. To apply an AutoML strategy that minimizes training time, use LatencyOptimized.

This parameter is only valid for predictors trained using AutoML.

Used to override the default evaluation parameters of the specified algorithm. Amazon Forecast evaluates a predictor by splitting a dataset into training data and testing data. The evaluation parameters define how to perform the split and the number of iterations.

An AWS Key Management Service (KMS) key and the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.

Specifies the forecast types used to train a predictor. You can specify up to five forecast types. Forecast types can be quantiles from 0.01 to 0.99, by increments of 0.01 or higher. You can also specify the mean forecast with mean.

The default value is ["0.10", "0.50", "0.9"].

Whether to perform hyperparameter optimization (HPO). HPO finds optimal hyperparameter values for your training data. The process of performing HPO is known as running a hyperparameter tuning job.

The default value is false. In this case, Amazon Forecast uses default hyperparameter values from the chosen algorithm.

To override the default values, set PerformHPO to true and, optionally, supply the HyperParameterTuningJobConfig object. The tuning job specifies a metric to optimize, which hyperparameters participate in tuning, and the valid range for each tunable hyperparameter. In this case, you are required to specify an algorithm and PerformAutoML must be false.

The following algorithms support HPO:

• DeepAR+
• CNN-QR

The optional metadata that you apply to the predictor 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.

A name for the predictor.

Specifies the number of time-steps that the model is trained to predict. The forecast horizon is also called the prediction length.

For example, if you configure a dataset for daily data collection (using the DataFrequency parameter of the CreateDataset operation) and set the forecast horizon to 10, the model returns predictions for 10 days.

The maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.

Describes the dataset group that contains the data to use to train the predictor.

The featurization configuration.

The Amazon Resource Name (ARN) of the predictor.

The response's http status code.

An array of filters. For each filter, provide a condition and a match statement. The condition is either IS or IS_NOT, which specifies whether to include or exclude the predictor backtest export jobs that match the statement from the list. The match statement consists of a key and a value.

Filter properties

• Condition - The condition to apply. Valid values are IS and IS_NOT. To include the predictor backtest export jobs that match the statement, specify IS. To exclude matching predictor backtest export jobs, specify IS_NOT.
• Key - The name of the parameter to filter on. Valid values are PredictorArn and Status.
• Value - The value to match.

If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

The number of items to return in the response.

Returns this token if the response is truncated. To retrieve the next set of results, use the token in the next request.

An array of objects that summarize the properties of each predictor backtest export job.

The response's http status code.

The Amazon Resource Name (ARN) of the predictor backtest export job to delete.

The quantiles at which probabilistic forecasts are generated. __You can currently specify up to 5 quantiles per forecast__. Accepted values include 0.01 to 0.99 (increments of .01 only) and mean. The mean forecast is different from the median (0.50) when the distribution is not symmetric (for example, Beta and Negative Binomial). The default value is ["0.1", "0.5", "0.9"].

The optional metadata that you apply to the forecast 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.

A name for the forecast.

The Amazon Resource Name (ARN) of the predictor to use to generate the forecast.

The Amazon Resource Name (ARN) of the forecast.

The response's http status code.

Optional metadata to help you categorize and organize your backtests. Each tag consists of a key and an optional value, both of which you define. Tag keys and values are case sensitive.

The following restrictions apply to tags:

• For each resource, each tag key must be unique and each tag key must have one value.
• Maximum number of tags per resource: 50.
• Maximum key length: 128 Unicode characters in UTF-8.
• Maximum value length: 256 Unicode characters in UTF-8.
• Accepted characters: all letters and numbers, spaces representable in UTF-8, and + - = . _ : / @. If your tagging schema is used across other services and resources, the character restrictions of those services also apply.
• Key prefixes cannot include any upper or lowercase combination of aws: or AWS:. Values can have this prefix. If a tag value has aws as its prefix but the key does not, 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. You cannot edit or delete tag keys with this prefix.

The name for the backtest export job.

The Amazon Resource Name (ARN) of the predictor that you want to export.

Undocumented member.

The Amazon Resource Name (ARN) of the predictor backtest export job that you want to export.

The response's http status code.

The Amazon Resource Name (ARN) of the forecast to delete.

The Amazon Resource Name (ARN) of the parent resource to delete. All child resources of the parent resource will also be deleted.

The Amazon Resource Name (ARN) of the dataset group.

When the dataset group was created.

An array of Amazon Resource Names (ARNs) of the datasets contained in the dataset group.

The status of the dataset group. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
• UPDATE_PENDING, UPDATE_IN_PROGRESS, UPDATE_FAILED

The UPDATE states apply when you call the UpdateDatasetGroup operation.

The Status of the dataset group must be ACTIVE before you can use the dataset group to create a predictor.

The domain associated with the dataset group.

The name of the dataset group.

The ARN of the dataset group.

When the dataset group was created or last updated from a call to the UpdateDatasetGroup operation. While the dataset group is being updated, LastModificationTime is the current time of the DescribeDatasetGroup call.

The response's http status code.

The Amazon Resource Name (ARN) that identifies the resource for which to list the tags. Currently, the supported resources are Forecast dataset groups, datasets, dataset import jobs, predictors, forecasts, and forecast export jobs.

The tags to add to the resource. A tag is an array of key-value pairs.

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.

The response's http status code.

If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

The number of items to return in the response.

If the response is truncated, Amazon Forecast returns this token. To retrieve the next set of results, use the token in the next request.

An array of objects that summarize each dataset's properties.

The response's http status code.

The Amazon Resource Name (ARN) of the predictor backtest export job.

When the predictor backtest export job was created.

The status of the predictor backtest export job. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• CREATE_STOPPING, CREATE_STOPPED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

Undocumented member.

The Amazon Resource Name (ARN) of the predictor.

The Amazon Resource Name (ARN) of the predictor backtest export job.

Information about any errors that may have occurred during the backtest export.

The name of the predictor backtest export job.

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

The response's http status code.

The Amazon Resource Name (ARN) that identifies the resource for which to list the tags. Currently, the supported resources are Forecast dataset groups, datasets, dataset import jobs, predictors, forecasts, and forecast exports.

The keys of the tags to be removed.

The response's http status code.

An array of Amazon Resource Names (ARNs) of the datasets that you want to include in the dataset group.

The optional metadata that you apply to the dataset group 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.

A name for the dataset group.

The domain associated with the dataset group. When you add a dataset to a dataset group, this value and the value specified for the Domain parameter of the CreateDataset operation must match.

The Domain and DatasetType that you choose determine the fields that must be present in training data that you import to a dataset. For example, if you choose the RETAIL domain and TARGET_TIME_SERIES as the DatasetType, Amazon Forecast requires that item_id, timestamp, and demand fields are present in your data. For more information, see howitworks-datasets-groups.

The Amazon Resource Name (ARN) of the dataset group.

The response's http status code.

An array of filters. For each filter, you provide a condition and a match statement. The condition is either IS or IS_NOT, which specifies whether to include or exclude the forecast export jobs that match the statement from the list, respectively. The match statement consists of a key and a value.

Filter properties

• Condition - The condition to apply. Valid values are IS and IS_NOT. To include the forecast export jobs that match the statement, specify IS. To exclude matching forecast export jobs, specify IS_NOT.
• Key - The name of the parameter to filter on. Valid values are ForecastArn and Status.
• Value - The value to match.

For example, to list all jobs that export a forecast named electricityforecast, specify the following filter:

"Filters": [ { "Condition": "IS", "Key": "ForecastArn", "Value": "arn:aws:forecast:us-west-2:<acct-id>:forecast/electricityforecast" } ]

If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

The number of items to return in the response.

If the response is truncated, Amazon Forecast returns this token. To retrieve the next set of results, use the token in the next request.

An array of objects that summarize each export job's properties.

The response's http status code.

An array of filters. For each filter, you provide a condition and a match statement. The condition is either IS or IS_NOT, which specifies whether to include or exclude the predictors that match the statement from the list, respectively. The match statement consists of a key and a value.

Filter properties

• Condition - The condition to apply. Valid values are IS and IS_NOT. To include the predictors that match the statement, specify IS. To exclude matching predictors, specify IS_NOT.
• Key - The name of the parameter to filter on. Valid values are DatasetGroupArn and Status.
• Value - The value to match.

For example, to list all predictors whose status is ACTIVE, you would specify:

"Filters": [ { "Condition": "IS", "Key": "Status", "Value": "ACTIVE" } ]

If the result of the previous request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

The number of items to return in the response.

If the response is truncated, Amazon Forecast returns this token. To retrieve the next set of results, use the token in the next request.

An array of objects that summarize each predictor's properties.

The response's http status code.

The name of the categorical hyperparameter to tune.

A list of the tunable categories for the hyperparameter.

The scale that hyperparameter tuning uses to search the hyperparameter range. Valid values:

Auto

Amazon Forecast hyperparameter tuning chooses the best scale for the hyperparameter.

Linear

Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.

Logarithmic

Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.

Logarithmic scaling works only for ranges that have values greater than 0.

ReverseLogarithmic

hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.

Reverse logarithmic scaling works only for ranges that are entirely within the range 0 <= x < 1.0.

For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:

The name of the hyperparameter to tune.

The maximum tunable value of the hyperparameter.

The minimum tunable value of the hyperparameter.

The path to an Amazon Simple Storage Service (Amazon S3) bucket along with the credentials to access the bucket.

The path to the training data stored in an Amazon Simple Storage Service (Amazon S3) bucket along with the credentials to access the data.

When the dataset group was created.

The name of the dataset group.

The Amazon Resource Name (ARN) of the dataset group.

When the dataset group was created or last updated from a call to the UpdateDatasetGroup operation. While the dataset group is being updated, LastModificationTime is the current time of the ListDatasetGroups call.

When the dataset import job was created.

The status of the dataset import job. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
• CREATE_STOPPING, CREATE_STOPPED

The name of the dataset import job.

The location of the training data to import and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data. The training data must be stored in an Amazon S3 bucket.

If encryption is used, DataSource includes an AWS Key Management Service (KMS) key.

The Amazon Resource Name (ARN) of the dataset import job.

If an error occurred, an informational message about the error.

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

When the dataset was created.

The Amazon Resource Name (ARN) of the dataset.

The domain associated with the dataset.

The dataset type.

The name of the dataset.

When you create a dataset, LastModificationTime is the same as CreationTime. While data is being imported to the dataset, LastModificationTime is the current time of the ListDatasets call. After a CreateDatasetImportJob operation has finished, LastModificationTime is when the import job completed or failed.

The ARN of the IAM role that Amazon Forecast can assume to access the AWS KMS key.

Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an InvalidInputException error.

The Amazon Resource Name (ARN) of the KMS key.

The Mean Absolute Scaled Error (MASE)

The weighted absolute percentage error (WAPE).

The Mean Absolute Percentage Error (MAPE)

The root-mean-square error (RMSE).

The Forecast type used to compute WAPE, MAPE, MASE, and RMSE.

The point from the end of the dataset where you want to split the data for model training and testing (evaluation). Specify the value as the number of data points. The default is the value of the forecast horizon. BackTestWindowOffset can be used to mimic a past virtual forecast start date. This value must be greater than or equal to the forecast horizon and less than half of the TARGET_TIME_SERIES dataset length.

ForecastHorizon <= BackTestWindowOffset < 1/2 * TARGET_TIME_SERIES dataset length

The number of times to split the input data. The default is 1. Valid values are 1 through 5.

The Amazon Resource Name (ARN) of the algorithm that was evaluated.

The array of test windows used for evaluating the algorithm. The NumberOfBacktestWindows from the EvaluationParameters object determines the number of windows in the array.

An array of one FeaturizationMethod object that specifies the feature transformation method.

The name of the schema attribute that specifies the data field to be featurized. Amazon Forecast supports the target field of the TARGET_TIME_SERIES and the RELATED_TIME_SERIES datasets. For example, for the RETAIL domain, the target is demand, and for the CUSTOM domain, the target is target_value. For more information, see howitworks-missing-values.

An array of featurization (transformation) information for the fields of a dataset.

An array of dimension (field) names that specify how to group the generated forecast.

For example, suppose that you are generating a forecast for item sales across all of your stores, and your dataset contains a store_id field. If you want the sales forecast for each item by store, you would specify store_id as the dimension.

All forecast dimensions specified in the TARGET_TIME_SERIES dataset don't need to be specified in the CreatePredictor request. All forecast dimensions specified in the RELATED_TIME_SERIES dataset must be specified in the CreatePredictor request.

The frequency of predictions in a forecast.

Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, "Y" indicates every year and "5min" indicates every five minutes.

The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset frequency.

When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to the RELATED_TIME_SERIES dataset frequency.

The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to override the default values. Related Time Series attributes do not accept aggregation parameters.

The following list shows the parameters and their valid values for the "filling" featurization method for a Target Time Series dataset. Bold signifies the default value.

• aggregation: sum, avg, first, min, max
• frontfill: none
• middlefill: zero, nan (not a number), value, median, mean, min, max
• backfill: zero, nan, value, median, mean, min, max

The following list shows the parameters and their valid values for a Related Time Series featurization method (there are no defaults):

• middlefill: zero, value, median, mean, min, max
• backfill: zero, value, median, mean, min, max
• futurefill: zero, value, median, mean, min, max

To set a filling method to a specific value, set the fill parameter to value and define the value in a corresponding _value parameter. For example, to set backfilling to a value of 2, include the following: "backfill": "value" and "backfill_value":"2".

The name of the method. The "filling" method is the only supported method.

The name of the parameter to filter on.

The value to match.

The condition to apply. To include the objects that match the statement, specify IS. To exclude matching objects, specify IS_NOT.

When the forecast export job was created.

The status of the forecast export job. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• CREATE_STOPPING, CREATE_STOPPED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

The Status of the forecast export job must be ACTIVE before you can access the forecast in your S3 bucket.

The path to the Amazon Simple Storage Service (Amazon S3) bucket where the forecast is exported.

The Amazon Resource Name (ARN) of the forecast export job.

The name of the forecast export job.

If an error occurred, an informational message about the error.

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

When the forecast creation task was created.

The status of the forecast. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• CREATE_STOPPING, CREATE_STOPPED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

The Status of the forecast must be ACTIVE before you can query or export the forecast.

The ARN of the predictor used to generate the forecast.

The ARN of the forecast.

The name of the forecast.

The Amazon Resource Name (ARN) of the dataset group that provided the data used to train the predictor.

If an error occurred, an informational message about the error.

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

Specifies the ranges of valid values for the hyperparameters.

An array of supplementary features. The only supported feature is a holiday calendar.

The Amazon Resource Name (ARN) of the dataset group.

The scale that hyperparameter tuning uses to search the hyperparameter range. Valid values:

Auto

Amazon Forecast hyperparameter tuning chooses the best scale for the hyperparameter.

Linear

Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.

Logarithmic

Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.

Logarithmic scaling works only for ranges that have values greater than 0.

ReverseLogarithmic

Not supported for IntegerParameterRange.

Reverse logarithmic scaling works only for ranges that are entirely within the range 0 <= x < 1.0.

For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:

The name of the hyperparameter to tune.

The maximum tunable value of the hyperparameter.

The minimum tunable value of the hyperparameter.

Provides detailed error metrics for each forecast type. Metrics include root-mean square-error (RMSE), mean absolute percentage error (MAPE), mean absolute scaled error (MASE), and weighted average percentage error (WAPE).

The root-mean-square error (RMSE).

An array of weighted quantile losses. Quantiles divide a probability distribution into regions of equal probability. The distribution in this case is the loss function.

The average value of all weighted quantile losses.

Specifies the tunable range for each categorical hyperparameter.

Specifies the tunable range for each integer hyperparameter.

Specifies the tunable range for each continuous hyperparameter.

When the predictor backtest export job was created.

The status of the predictor backtest export job. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• CREATE_STOPPING, CREATE_STOPPED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED

Undocumented member.

The Amazon Resource Name (ARN) of the predictor backtest export job.

Information about any errors that may have occurred during the backtest export.

The name of the predictor backtest export job.

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

The ARN of the algorithm used to test the predictor.

An array of test windows used to evaluate the algorithm. The NumberOfBacktestWindows from the object determines the number of windows in the array.

An array of the backtests performed to evaluate the accuracy of the predictor against a particular algorithm. The NumberOfBacktestWindows from the object determines the number of windows in the array.

When the model training task was created.

The status of the predictor. States include:

• ACTIVE

• CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
• DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
• CREATE_STOPPING, CREATE_STOPPED

The Status of the predictor must be ACTIVE before you can use the predictor to create a forecast.

The ARN of the predictor.

The name of the predictor.

The Amazon Resource Name (ARN) of the dataset group that contains the data used to train the predictor.

If an error occurred, an informational message about the error.

The last time the resource was modified. The timestamp depends on the status of the job:

• CREATE_PENDING - The CreationTime.
• CREATE_IN_PROGRESS - The current timestamp.
• CREATE_STOPPING - The current timestamp.
• CREATE_STOPPED - When the job stopped.
• ACTIVE or CREATE_FAILED - When the job finished or failed.

The Amazon Resource Name (ARN) of an AWS Key Management Service (KMS) key.

The path to an Amazon Simple Storage Service (Amazon S3) bucket or file(s) in an Amazon S3 bucket.

The ARN of the AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the Amazon S3 bucket or files. If you provide a value for the KMSKeyArn key, the role must allow access to the key.

Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an InvalidInputException error.

An array of attributes specifying the name and type of each field in a dataset.

The data type of the field.

The name of the dataset field.

For a numeric field, the maximum value in the field.

The number of null values in the field. CountNullLong is used instead of CountNull if the value is greater than 2,147,483,647.

The number of NAN (not a number) values in the field. If the response value is -1, refer to CountNanLong.

The number of NAN (not a number) values in the field. CountNanLong is used instead of CountNan if the value is greater than 2,147,483,647.

For a numeric field, the average value in the field.

The number of null values in the field. If the response value is -1, refer to CountNullLong.

The number of values in the field. If the response value is -1, refer to CountLong.

The number of values in the field. CountLong is used instead of Count if the value is greater than 2,147,483,647.

For a numeric field, the standard deviation.

For a numeric field, the minimum value in the field.

The number of distinct values in the field. CountDistinctLong is used instead of CountDistinct if the value is greater than 2,147,483,647.

The number of distinct values in the field. If the response value is -1, refer to CountDistinctLong.

The name of the feature. Valid values: "holiday" and "weather".

Weather Index

To enable the Weather Index, set the value to "true"

Holidays

To enable Holidays, specify a country with one of the following two-letter country codes:

• "AL" - ALBANIA
• "AR" - ARGENTINA
• "AT" - AUSTRIA
• "AU" - AUSTRALIA
• "BA" - BOSNIA HERZEGOVINA
• "BE" - BELGIUM
• "BG" - BULGARIA
• "BO" - BOLIVIA
• "BR" - BRAZIL
• "BY" - BELARUS
• "CA" - CANADA
• "CL" - CHILE
• "CO" - COLOMBIA
• "CR" - COSTA RICA
• "HR" - CROATIA
• "CZ" - CZECH REPUBLIC
• "DK" - DENMARK
• "EC" - ECUADOR
• "EE" - ESTONIA
• "ET" - ETHIOPIA
• "FI" - FINLAND
• "FR" - FRANCE
• "DE" - GERMANY
• "GR" - GREECE
• "HU" - HUNGARY
• "IS" - ICELAND
• "IN" - INDIA
• "IE" - IRELAND
• "IT" - ITALY
• "JP" - JAPAN
• "KZ" - KAZAKHSTAN
• "KR" - KOREA
• "LV" - LATVIA
• "LI" - LIECHTENSTEIN
• "LT" - LITHUANIA
• "LU" - LUXEMBOURG
• "MK" - MACEDONIA
• "MT" - MALTA
• "MX" - MEXICO
• "MD" - MOLDOVA
• "ME" - MONTENEGRO
• "NL" - NETHERLANDS
• "NZ" - NEW ZEALAND
• "NI" - NICARAGUA
• "NG" - NIGERIA
• "NO" - NORWAY
• "PA" - PANAMA
• "PY" - PARAGUAY
• "PE" - PERU
• "PL" - POLAND
• "PT" - PORTUGAL
• "RO" - ROMANIA
• "RU" - RUSSIA
• "RS" - SERBIA
• "SK" - SLOVAKIA
• "SI" - SLOVENIA
• "ZA" - SOUTH AFRICA
• "ES" - SPAIN
• "SE" - SWEDEN
• "CH" - SWITZERLAND
• "UA" - UKRAINE
• "AE" - UNITED ARAB EMIRATES
• "US" - UNITED STATES
• "UK" - UNITED KINGDOM
• "UY" - URUGUAY
• "VE" - VENEZUELA

One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

The optional part of a key-value pair that makes up a tag. A value acts as a descriptor within a tag category (key).

The status of the test. Possible status values are:

• ACTIVE

• CREATE_IN_PROGRESS

• CREATE_FAILED

The time at which the test ended.

The time at which the test began.

If the test failed, the reason why it failed.

The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

Provides metrics used to evaluate the performance of a predictor.

The timestamp that defines the end of the window.

The type of evaluation.

• SUMMARY - The average metrics across all windows.
• COMPUTED - The metrics for the specified window.

The timestamp that defines the start of the window.

The number of data points within the window.