String attributeName
The related time series that you are modifying. This value is case insensitive.
String operation
The operation that is applied to the provided attribute. Operations include:
ADD - adds Value to all rows of AttributeName.
SUBTRACT - subtracts Value from all rows of AttributeName.
MULTIPLY - multiplies all rows of AttributeName by Value.
DIVIDE - divides all rows of AttributeName by Value.
Double value
The value that is applied for the chosen Operation.
String name
The name of the additional dataset. Valid names: "holiday" and "weather".
Map<K,V> configuration
Weather Index
To enable the Weather Index, do not specify a value for Configuration.
Holidays
Holidays
To enable Holidays, set CountryCode to 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
String attributeName
The name of the attribute as specified in the schema. 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.
Map<K,V> transformations
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. Default values are bolded.
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".
PredictorBaseline predictorBaseline
The initial accuracy metrics for the predictor you are monitoring. Use these metrics as a baseline for comparison purposes as you use your predictor and the metrics change.
String name
The name of the hyperparameter to tune.
Double maxValue
The maximum tunable value of the hyperparameter.
Double minValue
The minimum tunable value of the hyperparameter.
String scalingType
The scale that hyperparameter tuning uses to search the hyperparameter range. Valid values:
Amazon Forecast hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
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.
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:
String predictorName
A unique name for the predictor
Integer forecastHorizon
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length.
The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the TARGET_TIME_SERIES dataset length. If you are retraining an existing AutoPredictor, then the maximum forecast horizon is the lesser of 500 time-steps or 1/3 of the TARGET_TIME_SERIES dataset length.
If you are upgrading to an AutoPredictor or retraining an existing AutoPredictor, you cannot update the forecast horizon parameter. You can meet this requirement by providing longer time-series in the dataset.
List<E> forecastTypes
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.
List<E> forecastDimensions
An array of dimension (field) names that specify how to group the generated forecast.
For example, if you are generating forecasts for item sales across all your stores, and your dataset contains a
store_id field, you would specify store_id as a dimension to group sales forecasts for
each store.
String forecastFrequency
The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".
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.
DataConfig dataConfig
The data configuration for your dataset group and any additional datasets.
EncryptionConfig encryptionConfig
String referencePredictorArn
The ARN of the predictor to retrain or upgrade. This parameter is only used when retraining or upgrading a predictor. When creating a new predictor, do not specify a value for this parameter.
When upgrading or retraining a predictor, only specify values for the ReferencePredictorArn and
PredictorName. The value for PredictorName must be a unique predictor name.
String optimizationMetric
The accuracy metric used to optimize the predictor.
Boolean explainPredictor
Create an Explainability resource for the predictor.
List<E> tags
Optional metadata to help you categorize and organize your predictors. 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.
MonitorConfig monitorConfig
The configuration details for predictor monitoring. Provide a name for the monitor resource to enable predictor monitoring.
Predictor monitoring allows you to see how your predictor's performance changes over time. For more information, see Predictor Monitoring.
TimeAlignmentBoundary timeAlignmentBoundary
The time boundary Forecast uses to align and aggregate any data that doesn't align with your forecast frequency. Provide the unit of time and the time boundary as a key value pair. For more information on specifying a time boundary, see Specifying a Time Boundary. If you don't provide a time boundary, Forecast uses a set of Default Time Boundaries.
String predictorArn
The Amazon Resource Name (ARN) of the predictor.
String datasetGroupName
A name for the dataset group.
String domain
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 Dataset
groups.
List<E> datasetArns
An array of Amazon Resource Names (ARNs) of the datasets that you want to include in the dataset group.
List<E> tags
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 Amazon Web Services 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.
String datasetGroupArn
The Amazon Resource Name (ARN) of the dataset group.
String datasetImportJobName
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.
String datasetArn
The Amazon Resource Name (ARN) of the Amazon Forecast dataset that you want to import data to.
DataSource dataSource
The location of the training data to import and an 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 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.
String timestampFormat
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".
String timeZone
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.
Boolean useGeolocationForTimeZone
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.
String geolocationFormat
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).
List<E> tags
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 Amazon Web Services 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.
String format
The format of the imported data, CSV or PARQUET. The default value is CSV.
String importMode
Specifies whether the dataset import job is a FULL or INCREMENTAL import. A
FULL dataset import replaces all of the existing data with the newly imported data. An
INCREMENTAL import appends the imported data to the existing data.
String datasetImportJobArn
The Amazon Resource Name (ARN) of the dataset import job.
String datasetName
A name for the dataset.
String domain
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 Importing datasets.
String datasetType
The dataset type. Valid values depend on the chosen Domain.
String dataFrequency
The frequency of data collection. This parameter is required for RELATED_TIME_SERIES datasets.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".
Schema schema
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 Dataset Domains and
Dataset Types.
EncryptionConfig encryptionConfig
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
List<E> tags
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 Amazon Web Services 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.
String datasetArn
The Amazon Resource Name (ARN) of the dataset.
String explainabilityExportName
A unique name for the Explainability export.
String explainabilityArn
The Amazon Resource Name (ARN) of the Explainability to export.
DataDestination destination
List<E> tags
Optional metadata to help you categorize and organize your resources. 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.
String format
The format of the exported data, CSV or PARQUET.
String explainabilityExportArn
The Amazon Resource Name (ARN) of the export.
String explainabilityName
A unique name for the Explainability.
String resourceArn
The Amazon Resource Name (ARN) of the Predictor or Forecast used to create the Explainability.
ExplainabilityConfig explainabilityConfig
The configuration settings that define the granularity of time series and time points for the Explainability.
DataSource dataSource
Schema schema
Boolean enableVisualization
Create an Explainability visualization that is viewable within the Amazon Web Services console.
String startDateTime
If TimePointGranularity is set to SPECIFIC, define the first point for the
Explainability.
Use the following timestamp format: yyyy-MM-ddTHH:mm:ss (example: 2015-01-01T20:00:00)
String endDateTime
If TimePointGranularity is set to SPECIFIC, define the last time point for the
Explainability.
Use the following timestamp format: yyyy-MM-ddTHH:mm:ss (example: 2015-01-01T20:00:00)
List<E> tags
Optional metadata to help you categorize and organize your resources. 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.
String explainabilityArn
The Amazon Resource Name (ARN) of the Explainability.
String forecastExportJobName
The name for the forecast export job.
String forecastArn
The Amazon Resource Name (ARN) of the forecast that you want to export.
DataDestination destination
The location where you want to save the forecast and an 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 Key Management Service (KMS) key. The IAM role
must allow Amazon Forecast permission to access the key.
List<E> tags
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 Amazon Web Services 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.
String format
The format of the exported data, CSV or PARQUET. The default value is CSV.
String forecastExportJobArn
The Amazon Resource Name (ARN) of the export job.
String forecastName
A name for the forecast.
String predictorArn
The Amazon Resource Name (ARN) of the predictor to use to generate the forecast.
List<E> forecastTypes
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 quantiles are the quantiles you specified during predictor creation. If you didn't specify quantiles,
the default values are ["0.1", "0.5", "0.9"].
List<E> tags
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 Amazon Web Services 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.
TimeSeriesSelector timeSeriesSelector
Defines the set of time series that are used to create the forecasts in a TimeSeriesIdentifiers
object.
The TimeSeriesIdentifiers object needs the following information:
DataSource
Format
Schema
String forecastArn
The Amazon Resource Name (ARN) of the forecast.
String monitorArn
The Amazon Resource Name (ARN) of the monitor resource.
String predictorBacktestExportJobName
The name for the backtest export job.
String predictorArn
The Amazon Resource Name (ARN) of the predictor that you want to export.
DataDestination destination
List<E> tags
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.
String format
The format of the exported data, CSV or PARQUET. The default value is CSV.
String predictorBacktestExportJobArn
The Amazon Resource Name (ARN) of the predictor backtest export job that you want to export.
String predictorName
A name for the predictor.
String algorithmArn
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
Integer forecastHorizon
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.
List<E> forecastTypes
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"].
Boolean performAutoML
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.
String autoMLOverrideStrategy
The LatencyOptimized AutoML override strategy is only available in private beta. Contact Amazon Web
Services 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.
Boolean performHPO
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
Map<K,V> trainingParameters
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.
EvaluationParameters evaluationParameters
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.
HyperParameterTuningJobConfig hPOConfig
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.
InputDataConfig inputDataConfig
Describes the dataset group that contains the data to use to train the predictor.
FeaturizationConfig featurizationConfig
The featurization configuration.
EncryptionConfig encryptionConfig
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
List<E> tags
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 Amazon Web Services 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.
String optimizationMetric
The accuracy metric used to optimize the predictor.
String predictorArn
The Amazon Resource Name (ARN) of the predictor.
String whatIfAnalysisName
The name of the what-if analysis. Each name must be unique.
String forecastArn
The Amazon Resource Name (ARN) of the baseline forecast.
TimeSeriesSelector timeSeriesSelector
Defines the set of time series that are used in the what-if analysis with a TimeSeriesIdentifiers
object. What-if analyses are performed only for the time series in this object.
The TimeSeriesIdentifiers object needs the following information:
DataSource
Format
Schema
List<E> tags
A list of tags to apply to the what if forecast.
String whatIfAnalysisArn
The Amazon Resource Name (ARN) of the what-if analysis.
String whatIfForecastExportName
The name of the what-if forecast to export.
List<E> whatIfForecastArns
The list of what-if forecast Amazon Resource Names (ARNs) to export.
DataDestination destination
The location where you want to save the forecast and an 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 Key Management Service (KMS) key. The IAM role
must allow Amazon Forecast permission to access the key.
List<E> tags
A list of tags to apply to the what if forecast.
String format
The format of the exported data, CSV or PARQUET.
String whatIfForecastExportArn
The Amazon Resource Name (ARN) of the what-if forecast.
String whatIfForecastName
The name of the what-if forecast. Names must be unique within each what-if analysis.
String whatIfAnalysisArn
The Amazon Resource Name (ARN) of the what-if analysis.
List<E> timeSeriesTransformations
The transformations that are applied to the baseline time series. Each transformation contains an action and a set of conditions. An action is applied only when all conditions are met. If no conditions are provided, the action is applied to all items.
TimeSeriesReplacementsDataSource timeSeriesReplacementsDataSource
The replacement time series dataset, which contains the rows that you want to change in the related time series dataset. A replacement time series does not need to contain all rows that are in the baseline related time series. Include only the rows (measure-dimension combinations) that you want to include in the what-if forecast.
This dataset is merged with the original time series to create a transformed dataset that is used for the what-if analysis.
This dataset should contain the items to modify (such as item_id or workforce_type), any relevant dimensions, the timestamp column, and at least one of the related time series columns. This file should not contain duplicate timestamps for the same time series.
Timestamps and item_ids not included in this dataset are not included in the what-if analysis.
List<E> tags
A list of tags to apply to the what if forecast.
String whatIfForecastArn
The Amazon Resource Name (ARN) of the what-if forecast.
String datasetGroupArn
The ARN of the dataset group used to train the predictor.
List<E> attributeConfigs
Aggregation and filling options for attributes in your dataset group.
List<E> additionalDatasets
Additional built-in datasets like Holidays and the Weather Index.
S3Config s3Config
The path to an Amazon Simple Storage Service (Amazon S3) bucket along with the credentials to access the bucket.
String datasetGroupArn
The Amazon Resource Name (ARN) of the dataset group.
String datasetGroupName
The name of the dataset group.
Date creationTime
When the dataset group was created.
Date lastModificationTime
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.
String datasetImportJobArn
The Amazon Resource Name (ARN) of the dataset import job.
String datasetImportJobName
The name of the dataset import job.
DataSource dataSource
The location of the training data to import and an 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 Key Management Service (KMS) key.
String status
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
String message
If an error occurred, an informational message about the error.
Date creationTime
When the dataset import job was created.
Date lastModificationTime
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.
String importMode
The import mode of the dataset import job, FULL or INCREMENTAL.
String datasetArn
The Amazon Resource Name (ARN) of the dataset.
String datasetName
The name of the dataset.
String datasetType
The dataset type.
String domain
The domain associated with the dataset.
Date creationTime
When the dataset was created.
Date lastModificationTime
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.
S3Config s3Config
The path to the data stored in an Amazon Simple Storage Service (Amazon S3) bucket along with the credentials to access the data.
String datasetGroupArn
The Amazon Resource Name (ARN) of the dataset group to delete.
String datasetImportJobArn
The Amazon Resource Name (ARN) of the dataset import job to delete.
String datasetArn
The Amazon Resource Name (ARN) of the dataset to delete.
String explainabilityExportArn
The Amazon Resource Name (ARN) of the Explainability export to delete.
String explainabilityArn
The Amazon Resource Name (ARN) of the Explainability resource to delete.
String forecastExportJobArn
The Amazon Resource Name (ARN) of the forecast export job to delete.
String forecastArn
The Amazon Resource Name (ARN) of the forecast to delete.
String monitorArn
The Amazon Resource Name (ARN) of the monitor resource to delete.
String predictorBacktestExportJobArn
The Amazon Resource Name (ARN) of the predictor backtest export job to delete.
String predictorArn
The Amazon Resource Name (ARN) of the predictor to delete.
String resourceArn
The Amazon Resource Name (ARN) of the parent resource to delete. All child resources of the parent resource will also be deleted.
String whatIfAnalysisArn
The Amazon Resource Name (ARN) of the what-if analysis that you want to delete.
String whatIfForecastExportArn
The Amazon Resource Name (ARN) of the what-if forecast export that you want to delete.
String whatIfForecastArn
The Amazon Resource Name (ARN) of the what-if forecast that you want to delete.
String predictorArn
The Amazon Resource Name (ARN) of the predictor.
String predictorArn
The Amazon Resource Name (ARN) of the predictor
String predictorName
The name of the predictor.
Integer forecastHorizon
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length.
List<E> forecastTypes
The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"].
String forecastFrequency
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.
List<E> forecastDimensions
An array of dimension (field) names that specify the attributes used to group your time series.
List<E> datasetImportJobArns
An array of the ARNs of the dataset import jobs used to import training data for the predictor.
DataConfig dataConfig
The data configuration for your dataset group and any additional datasets.
EncryptionConfig encryptionConfig
ReferencePredictorSummary referencePredictorSummary
The ARN and state of the reference predictor. This parameter is only valid for retrained or upgraded predictors.
Long estimatedTimeRemainingInMinutes
The estimated time remaining in minutes for the predictor training job to complete.
String status
The status of the predictor. States include:
ACTIVE
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
CREATE_STOPPING, CREATE_STOPPED
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
String message
In the event of an error, a message detailing the cause of the error.
Date creationTime
The timestamp of the CreateAutoPredictor request.
Date lastModificationTime
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.
String optimizationMetric
The accuracy metric used to optimize the predictor.
ExplainabilityInfo explainabilityInfo
Provides the status and ARN of the Predictor Explainability.
MonitorInfo monitorInfo
A object with the Amazon Resource Name (ARN) and status of the monitor resource.
TimeAlignmentBoundary timeAlignmentBoundary
The time boundary Forecast uses when aggregating data.
String datasetGroupArn
The Amazon Resource Name (ARN) of the dataset group.
String datasetGroupName
The name of the dataset group.
String datasetGroupArn
The ARN of the dataset group.
List<E> datasetArns
An array of Amazon Resource Names (ARNs) of the datasets contained in the dataset group.
String domain
The domain associated with the dataset group.
String status
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.
Date creationTime
When the dataset group was created.
Date lastModificationTime
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.
String datasetImportJobArn
The Amazon Resource Name (ARN) of the dataset import job.
String datasetImportJobName
The name of the dataset import job.
String datasetImportJobArn
The ARN of the dataset import job.
String datasetArn
The Amazon Resource Name (ARN) of the dataset that the training data was imported to.
String timestampFormat
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
String timeZone
The single time zone applied to every item in the dataset
Boolean useGeolocationForTimeZone
Whether TimeZone is automatically derived from the geolocation attribute.
String geolocationFormat
The format of the geolocation attribute. Valid Values:"LAT_LONG" and "CC_POSTALCODE".
DataSource dataSource
The location of the training data to import and an Identity and Access Management (IAM) role that Amazon Forecast can assume to access the data.
If encryption is used, DataSource includes an Key Management Service (KMS) key.
Long estimatedTimeRemainingInMinutes
The estimated time remaining in minutes for the dataset import job to complete.
Map<K,V> fieldStatistics
Statistical information about each field in the input data.
Double dataSize
The size of the dataset in gigabytes (GB) after the import job has finished.
String status
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
String message
If an error occurred, an informational message about the error.
Date creationTime
When the dataset import job was created.
Date lastModificationTime
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.
String format
The format of the imported data, CSV or PARQUET.
String importMode
The import mode of the dataset import job, FULL or INCREMENTAL.
String datasetArn
The Amazon Resource Name (ARN) of the dataset.
String datasetArn
The Amazon Resource Name (ARN) of the dataset.
String datasetName
The name of the dataset.
String domain
The domain associated with the dataset.
String datasetType
The dataset type.
String dataFrequency
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.
Schema schema
An array of SchemaAttribute objects that specify the dataset fields. Each
SchemaAttribute specifies the name and data type of a field.
EncryptionConfig encryptionConfig
The Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
String status
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.
Date creationTime
When the dataset was created.
Date lastModificationTime
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.
String explainabilityExportArn
The Amazon Resource Name (ARN) of the Explainability export.
String explainabilityExportArn
The Amazon Resource Name (ARN) of the Explainability export.
String explainabilityExportName
The name of the Explainability export.
String explainabilityArn
The Amazon Resource Name (ARN) of the Explainability export.
DataDestination destination
String message
Information about any errors that occurred during the export.
String status
The status of the Explainability export. States include:
ACTIVE
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
CREATE_STOPPING, CREATE_STOPPED
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
Date creationTime
When the Explainability export was created.
Date lastModificationTime
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.
String format
The format of the exported data, CSV or PARQUET.
String explainabilityArn
The Amazon Resource Name (ARN) of the Explaianability to describe.
String explainabilityArn
The Amazon Resource Name (ARN) of the Explainability.
String explainabilityName
The name of the Explainability.
String resourceArn
The Amazon Resource Name (ARN) of the Predictor or Forecast used to create the Explainability resource.
ExplainabilityConfig explainabilityConfig
The configuration settings that define the granularity of time series and time points for the Explainability.
Boolean enableVisualization
Whether the visualization was enabled for the Explainability resource.
DataSource dataSource
Schema schema
String startDateTime
If TimePointGranularity is set to SPECIFIC, the first time point in the Explainability.
String endDateTime
If TimePointGranularity is set to SPECIFIC, the last time point in the Explainability.
Long estimatedTimeRemainingInMinutes
The estimated time remaining in minutes for the CreateExplainability job to complete.
String message
If an error occurred, a message about the error.
String status
The status of the Explainability resource. States include:
ACTIVE
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
CREATE_STOPPING, CREATE_STOPPED
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
Date creationTime
When the Explainability resource was created.
Date lastModificationTime
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.
String forecastExportJobArn
The Amazon Resource Name (ARN) of the forecast export job.
String forecastExportJobArn
The ARN of the forecast export job.
String forecastExportJobName
The name of the forecast export job.
String forecastArn
The Amazon Resource Name (ARN) of the exported forecast.
DataDestination destination
The path to the Amazon Simple Storage Service (Amazon S3) bucket where the forecast is exported.
String message
If an error occurred, an informational message about the error.
String status
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.
Date creationTime
When the forecast export job was created.
Date lastModificationTime
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.
String format
The format of the exported data, CSV or PARQUET.
String forecastArn
The Amazon Resource Name (ARN) of the forecast.
String forecastArn
The forecast ARN as specified in the request.
String forecastName
The name of the forecast.
List<E> forecastTypes
The quantiles at which probabilistic forecasts were generated.
String predictorArn
The ARN of the predictor used to generate the forecast.
String datasetGroupArn
The ARN of the dataset group that provided the data used to train the predictor.
Long estimatedTimeRemainingInMinutes
The estimated time remaining in minutes for the forecast job to complete.
String status
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.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the forecast creation task was created.
Date lastModificationTime
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.
TimeSeriesSelector timeSeriesSelector
The time series to include in the forecast.
String monitorArn
The Amazon Resource Name (ARN) of the monitor resource to describe.
String monitorName
The name of the monitor.
String monitorArn
The Amazon Resource Name (ARN) of the monitor resource described.
String resourceArn
The Amazon Resource Name (ARN) of the auto predictor being monitored.
String status
The status of the monitor resource.
Date lastEvaluationTime
The timestamp of the latest evaluation completed by the monitor.
String lastEvaluationState
The state of the monitor's latest evaluation.
Baseline baseline
Metrics you can use as a baseline for comparison purposes. Use these values you interpret monitoring results for an auto predictor.
String message
An error message, if any, for the monitor.
Date creationTime
The timestamp for when the monitor resource was created.
Date lastModificationTime
The timestamp of the latest modification to the monitor.
Long estimatedEvaluationTimeRemainingInMinutes
The estimated number of minutes remaining before the monitor resource finishes its current evaluation.
String predictorBacktestExportJobArn
The Amazon Resource Name (ARN) of the predictor backtest export job.
String predictorBacktestExportJobArn
The Amazon Resource Name (ARN) of the predictor backtest export job.
String predictorBacktestExportJobName
The name of the predictor backtest export job.
String predictorArn
The Amazon Resource Name (ARN) of the predictor.
DataDestination destination
String message
Information about any errors that may have occurred during the backtest export.
String status
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
Date creationTime
When the predictor backtest export job was created.
Date lastModificationTime
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.
String format
The format of the exported data, CSV or PARQUET.
String predictorArn
The Amazon Resource Name (ARN) of the predictor that you want information about.
String predictorArn
The ARN of the predictor.
String predictorName
The name of the predictor.
String algorithmArn
The Amazon Resource Name (ARN) of the algorithm used for model training.
List<E> autoMLAlgorithmArns
When PerformAutoML is specified, the ARN of the chosen algorithm.
Integer forecastHorizon
The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
List<E> forecastTypes
The forecast types used during predictor training. Default value is ["0.1","0.5","0.9"]
Boolean performAutoML
Whether the predictor is set to perform AutoML.
String autoMLOverrideStrategy
The LatencyOptimized AutoML override strategy is only available in private beta. Contact Amazon Web
Services 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.
Boolean performHPO
Whether the predictor is set to perform hyperparameter optimization (HPO).
Map<K,V> trainingParameters
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.
EvaluationParameters evaluationParameters
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.
HyperParameterTuningJobConfig hPOConfig
The hyperparameter override values for the algorithm.
InputDataConfig inputDataConfig
Describes the dataset group that contains the data to use to train the predictor.
FeaturizationConfig featurizationConfig
The featurization configuration.
EncryptionConfig encryptionConfig
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
PredictorExecutionDetails predictorExecutionDetails
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.
Long estimatedTimeRemainingInMinutes
The estimated time remaining in minutes for the predictor training job to complete.
Boolean isAutoPredictor
Whether the predictor was created with CreateAutoPredictor.
List<E> datasetImportJobArns
An array of the ARNs of the dataset import jobs used to import training data for the predictor.
String status
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.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the model training task was created.
Date lastModificationTime
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.
String optimizationMetric
The accuracy metric used to optimize the predictor.
String whatIfAnalysisArn
The Amazon Resource Name (ARN) of the what-if analysis that you are interested in.
String whatIfAnalysisName
The name of the what-if analysis.
String whatIfAnalysisArn
The Amazon Resource Name (ARN) of the what-if analysis.
String forecastArn
The Amazon Resource Name (ARN) of the what-if forecast.
Long estimatedTimeRemainingInMinutes
The approximate time remaining to complete the what-if analysis, in minutes.
String status
The status of the what-if analysis. 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 what-if analysis must be ACTIVE before you can access the analysis.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the what-if analysis was created.
Date lastModificationTime
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.
TimeSeriesSelector timeSeriesSelector
String whatIfForecastExportArn
The Amazon Resource Name (ARN) of the what-if forecast export that you are interested in.
String whatIfForecastExportArn
The Amazon Resource Name (ARN) of the what-if forecast export.
String whatIfForecastExportName
The name of the what-if forecast export.
List<E> whatIfForecastArns
An array of Amazon Resource Names (ARNs) that represent all of the what-if forecasts exported in this resource.
DataDestination destination
String message
If an error occurred, an informational message about the error.
String status
The status of the what-if 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 what-if forecast export must be ACTIVE before you can access the
forecast export.
Date creationTime
When the what-if forecast export was created.
Long estimatedTimeRemainingInMinutes
The approximate time remaining to complete the what-if forecast export, in minutes.
Date lastModificationTime
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.
String format
The format of the exported data, CSV or PARQUET.
String whatIfForecastArn
The Amazon Resource Name (ARN) of the what-if forecast that you are interested in.
String whatIfForecastName
The name of the what-if forecast.
String whatIfForecastArn
The Amazon Resource Name (ARN) of the what-if forecast.
String whatIfAnalysisArn
The Amazon Resource Name (ARN) of the what-if analysis that contains this forecast.
Long estimatedTimeRemainingInMinutes
The approximate time remaining to complete the what-if forecast, in minutes.
String status
The status of the what-if 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 what-if forecast must be ACTIVE before you can access the forecast.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the what-if forecast was created.
Date lastModificationTime
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.
List<E> timeSeriesTransformations
An array of Action and TimeSeriesConditions elements that describe what transformations
were applied to which time series.
TimeSeriesReplacementsDataSource timeSeriesReplacementsDataSource
An array of S3Config, Schema, and Format elements that describe the
replacement time series.
List<E> forecastTypes
The quantiles at which probabilistic forecasts are generated. You can specify up to five quantiles per what-if
forecast in the CreateWhatIfForecast operation. If you didn't specify quantiles, the default values are
["0.1", "0.5", "0.9"].
String roleArn
The ARN of the IAM role that Amazon Forecast can assume to access the KMS key.
Passing a role across Amazon Web Services accounts is not allowed. If you pass a role that isn't in your account,
you get an InvalidInputException error.
String kMSKeyArn
The Amazon Resource Name (ARN) of the KMS key.
String forecastType
The Forecast type used to compute WAPE, MAPE, MASE, and RMSE.
Double wAPE
The weighted absolute percentage error (WAPE).
Double rMSE
The root-mean-square error (RMSE).
Double mASE
The Mean Absolute Scaled Error (MASE)
Double mAPE
The Mean Absolute Percentage Error (MAPE)
Integer numberOfBacktestWindows
The number of times to split the input data. The default is 1. Valid values are 1 through 5.
Integer backTestWindowOffset
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
String algorithmArn
The Amazon Resource Name (ARN) of the algorithm that was evaluated.
List<E> testWindows
The array of test windows used for evaluating the algorithm. The NumberOfBacktestWindows from the
EvaluationParameters object determines the number of windows in the array.
String timeSeriesGranularity
To create an Explainability for all time series in your datasets, use ALL. To create an
Explainability for specific time series in your datasets, use SPECIFIC.
Specify time series by uploading a CSV or Parquet file to an Amazon S3 bucket and set the location within the DataDestination data type.
String timePointGranularity
To create an Explainability for all time points in your forecast horizon, use ALL. To create an
Explainability for specific time points in your forecast horizon, use SPECIFIC.
Specify time points with the StartDateTime and EndDateTime parameters within the
CreateExplainability operation.
String explainabilityExportArn
The Amazon Resource Name (ARN) of the Explainability export.
String explainabilityExportName
The name of the Explainability export
DataDestination destination
String status
The status of the Explainability export. States include:
ACTIVE
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
CREATE_STOPPING, CREATE_STOPPED
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
String message
Information about any errors that may have occurred during the Explainability export.
Date creationTime
When the Explainability was created.
Date lastModificationTime
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.
String explainabilityArn
The Amazon Resource Name (ARN) of the Explainability.
String status
The status of the Explainability. States include:
ACTIVE
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
CREATE_STOPPING, CREATE_STOPPED
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
String explainabilityArn
The Amazon Resource Name (ARN) of the Explainability.
String explainabilityName
The name of the Explainability.
String resourceArn
The Amazon Resource Name (ARN) of the Predictor or Forecast used to create the Explainability.
ExplainabilityConfig explainabilityConfig
The configuration settings that define the granularity of time series and time points for the Explainability.
String status
The status of the Explainability. States include:
ACTIVE
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
CREATE_STOPPING, CREATE_STOPPED
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
String message
Information about any errors that may have occurred during the Explainability creation process.
Date creationTime
When the Explainability was created.
Date lastModificationTime
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.
String attributeName
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.
List<E> featurizationPipeline
An array of one FeaturizationMethod object that specifies the feature transformation method.
String forecastFrequency
The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M".
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 TARGET_TIME_SERIES dataset frequency.
List<E> forecastDimensions
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.
List<E> featurizations
An array of featurization (transformation) information for the fields of a dataset.
String featurizationMethodName
The name of the method. The "filling" method is the only supported method.
Map<K,V> featurizationMethodParameters
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".
String forecastExportJobArn
The Amazon Resource Name (ARN) of the forecast export job.
String forecastExportJobName
The name of the forecast export job.
DataDestination destination
The path to the Amazon Simple Storage Service (Amazon S3) bucket where the forecast is exported.
String status
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.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the forecast export job was created.
Date lastModificationTime
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.
String forecastArn
The ARN of the forecast.
String forecastName
The name of the forecast.
String predictorArn
The ARN of the predictor used to generate the forecast.
Boolean createdUsingAutoPredictor
Whether the Forecast was created from an AutoPredictor.
String datasetGroupArn
The Amazon Resource Name (ARN) of the dataset group that provided the data used to train the predictor.
String status
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.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the forecast creation task was created.
Date lastModificationTime
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.
String predictorArn
The Amazon Resource Name (ARN) of the predictor to get metrics for.
List<E> predictorEvaluationResults
An array of results from evaluating the predictor.
Boolean isAutoPredictor
Whether the predictor was created with CreateAutoPredictor.
String autoMLOverrideStrategy
The LatencyOptimized AutoML override strategy is only available in private beta. Contact Amazon Web
Services 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.
String optimizationMetric
The accuracy metric used to optimize the predictor.
ParameterRanges parameterRanges
Specifies the ranges of valid values for the hyperparameters.
String name
The name of the hyperparameter to tune.
Integer maxValue
The maximum tunable value of the hyperparameter.
Integer minValue
The minimum tunable value of the hyperparameter.
String scalingType
The scale that hyperparameter tuning uses to search the hyperparameter range. Valid values:
Amazon Forecast hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
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.
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:
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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" } ]
String nextToken
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.
Integer maxResults
The number of items returned in the response.
List<E> filters
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 resources 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.
Key - The name of the parameter to filter on. Valid values are ResourceArn and
Status.
Value - The value to match.
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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 resources 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.
Key - The name of the parameter to filter on. Valid values are ResourceArn and
Status.
Value - The value to match.
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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" } ]
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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" } ]
String nextToken
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.
Integer maxResults
The maximum number of monitoring results to return.
String monitorArn
The Amazon Resource Name (ARN) of the monitor resource to get results from.
List<E> filters
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 resources 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.
Key - The name of the parameter to filter on. The only valid value is EvaluationState.
Value - The value to match. Valid values are only SUCCESS or FAILURE.
For example, to list only successful monitor evaluations, you would specify:
"Filters": [ { "Condition": "IS", "Key": "EvaluationState", "Value": "SUCCESS" } ]
String nextToken
If the response is truncated, Amazon Forecast returns this token. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.
List<E> predictorMonitorEvaluations
The monitoring results and predictor events collected by the monitor resource during different windows of time.
For information about monitoring see Viewing Monitoring Results. For more information about retrieving monitoring results see Viewing Monitoring Results.
String nextToken
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.
Integer maxResults
The maximum number of monitors to include in the response.
List<E> filters
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 resources 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.
Key - The name of the parameter to filter on. The only valid value is Status.
Value - The value to match.
For example, to list all monitors who's status is ACTIVE, you would specify:
"Filters": [ { "Condition": "IS", "Key": "Status", "Value": "ACTIVE" } ]
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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.
List<E> predictorBacktestExportJobs
An array of objects that summarize the properties of each predictor backtest export job.
String nextToken
Returns this token if the response is truncated. To retrieve the next set of results, use the token in the next request.
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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" } ]
String resourceArn
The Amazon Resource Name (ARN) that identifies the resource for which to list the tags.
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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 what-if analysis 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 what-if analysis jobs that match the statement, specify IS. To exclude matching what-if
analysis jobs, specify IS_NOT.
Key - The name of the parameter to filter on. Valid values are WhatIfAnalysisArn and
Status.
Value - The value to match.
For example, to list all jobs that export a forecast named electricityWhatIf, specify the following filter:
"Filters": [ { "Condition": "IS", "Key": "WhatIfAnalysisArn", "Value": "arn:aws:forecast:us-west-2:<acct-id>:forecast/electricityWhatIf" } ]
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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 what-if 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 WhatIfForecastExportArn
and Status.
Value - The value to match.
For example, to list all jobs that export a forecast named electricityWIFExport, specify the following filter:
"Filters": [ { "Condition": "IS", "Key": "WhatIfForecastExportArn", "Value": "arn:aws:forecast:us-west-2:<acct-id>:forecast/electricityWIFExport" } ]
String nextToken
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.
Integer maxResults
The number of items to return in the response.
List<E> filters
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 what-if 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 WhatIfForecastArn and
Status.
Value - The value to match.
For example, to list all jobs that export a forecast named electricityWhatIfForecast, specify the following filter:
"Filters": [ { "Condition": "IS", "Key": "WhatIfForecastArn", "Value": "arn:aws:forecast:us-west-2:<acct-id>:forecast/electricityWhatIfForecast" } ]
List<E> whatIfForecasts
An array of WhatIfForecasts objects that describe the matched forecasts.
String nextToken
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.
Double rMSE
The root-mean-square error (RMSE).
List<E> weightedQuantileLosses
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.
List<E> errorMetrics
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).
Double averageWeightedQuantileLoss
The average value of all weighted quantile losses.
String monitorName
The name of the monitor resource.
String datasetImportJobArn
The Amazon Resource Name (ARN) of the dataset import job used to import the data that initiated the monitor evaluation.
String forecastArn
The Amazon Resource Name (ARN) of the forecast the monitor used during the evaluation.
String predictorArn
The Amazon Resource Name (ARN) of the predictor resource you are monitoring.
String monitorArn
The Amazon Resource Name (ARN) of the monitor resource.
String status
The status of the monitor. States include:
ACTIVE
ACTIVE_STOPPING, ACTIVE_STOPPED
UPDATE_IN_PROGRESS
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
String monitorArn
The Amazon Resource Name (ARN) of the monitor resource.
String monitorName
The name of the monitor resource.
String resourceArn
The Amazon Resource Name (ARN) of the predictor being monitored.
String status
The status of the monitor. States include:
ACTIVE
ACTIVE_STOPPING, ACTIVE_STOPPED
UPDATE_IN_PROGRESS
CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED
DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED
Date creationTime
When the monitor resource was created.
Date lastModificationTime
The last time the monitor resource was modified. The timestamp depends on the status of the job:
CREATE_PENDING - The CreationTime.
CREATE_IN_PROGRESS - The current timestamp.
STOPPED - When the resource stopped.
ACTIVE or CREATE_FAILED - When the monitor creation finished or failed.
List<E> categoricalParameterRanges
Specifies the tunable range for each categorical hyperparameter.
List<E> continuousParameterRanges
Specifies the tunable range for each continuous hyperparameter.
List<E> integerParameterRanges
Specifies the tunable range for each integer hyperparameter.
String predictorBacktestExportJobArn
The Amazon Resource Name (ARN) of the predictor backtest export job.
String predictorBacktestExportJobName
The name of the predictor backtest export job.
DataDestination destination
String status
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
String message
Information about any errors that may have occurred during the backtest export.
Date creationTime
When the predictor backtest export job was created.
Date lastModificationTime
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.
List<E> baselineMetrics
The initial accuracy metrics for the predictor. Use these metrics as a baseline for comparison purposes as you use your predictor and the metrics change.
String detail
The type of event. For example, Retrain. A retraining event denotes the timepoint when a predictor
was retrained. Any monitor results from before the Datetime are from the previous predictor. Any new
metrics are for the newly retrained predictor.
Date datetime
The timestamp for when the event occurred.
String resourceArn
The Amazon Resource Name (ARN) of the resource to monitor.
String monitorArn
The Amazon Resource Name (ARN) of the monitor resource.
Date evaluationTime
The timestamp that indicates when the monitor evaluation was started.
String evaluationState
The status of the monitor evaluation. The state can be SUCCESS or FAILURE.
Date windowStartDatetime
The timestamp that indicates the start of the window that is used for monitor evaluation.
Date windowEndDatetime
The timestamp that indicates the end of the window that is used for monitor evaluation.
PredictorEvent predictorEvent
Provides details about a predictor event, such as a retraining.
MonitorDataSource monitorDataSource
The source of the data the monitor resource used during the evaluation.
List<E> metricResults
A list of metrics Forecast calculated when monitoring a predictor. You can compare the value for each metric in the list to the metric's value in the Baseline to see how your predictor's performance is changing.
Long numItemsEvaluated
The number of items considered during the evaluation.
String message
Information about any errors that may have occurred during the monitor evaluation.
String predictorArn
The ARN of the predictor.
String predictorName
The name of the predictor.
String datasetGroupArn
The Amazon Resource Name (ARN) of the dataset group that contains the data used to train the predictor.
Boolean isAutoPredictor
Whether AutoPredictor was used to create the predictor.
ReferencePredictorSummary referencePredictorSummary
A summary of the reference predictor used if the predictor was retrained or upgraded.
String status
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.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the model training task was created.
Date lastModificationTime
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.
String resourceArn
The Amazon Resource Name (ARN) of the monitor resource to resume.
String path
The path to an Amazon Simple Storage Service (Amazon S3) bucket or file(s) in an Amazon S3 bucket.
String roleArn
The ARN of the 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 Amazon Web Services accounts is not allowed. If you pass a role that isn't in your account,
you get an InvalidInputException error.
String kMSKeyArn
The Amazon Resource Name (ARN) of an Key Management Service (KMS) key.
Integer count
The number of values in the field. If the response value is -1, refer to CountLong.
Integer countDistinct
The number of distinct values in the field. If the response value is -1, refer to CountDistinctLong.
Integer countNull
The number of null values in the field. If the response value is -1, refer to CountNullLong.
Integer countNan
The number of NAN (not a number) values in the field. If the response value is -1, refer to
CountNanLong.
String min
For a numeric field, the minimum value in the field.
String max
For a numeric field, the maximum value in the field.
Double avg
For a numeric field, the average value in the field.
Double stddev
For a numeric field, the standard deviation.
Long countLong
The number of values in the field. CountLong is used instead of Count if the value is
greater than 2,147,483,647.
Long countDistinctLong
The number of distinct values in the field. CountDistinctLong is used instead of
CountDistinct if the value is greater than 2,147,483,647.
Long countNullLong
The number of null values in the field. CountNullLong is used instead of CountNull if
the value is greater than 2,147,483,647.
Long 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.
String resourceArn
The Amazon Resource Name (ARN) that identifies the resource to stop. The supported ARNs are
DatasetImportJobArn, PredictorArn, PredictorBacktestExportJobArn,
ForecastArn, ForecastExportJobArn, ExplainabilityArn, and
ExplainabilityExportArn.
String name
The name of the feature. Valid values: "holiday" and "weather".
String value
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
String resourceArn
The Amazon Resource Name (ARN) that identifies the resource for which to list the tags.
List<E> tags
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 Amazon Web Services 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.
Date testWindowStart
The time at which the test began.
Date testWindowEnd
The time at which the test ended.
String status
The status of the test. Possible status values are:
ACTIVE
CREATE_IN_PROGRESS
CREATE_FAILED
String message
If the test failed, the reason why it failed.
String month
The month to use for time alignment during aggregation. The month must be in uppercase.
Integer dayOfMonth
The day of the month to use for time alignment during aggregation.
String dayOfWeek
The day of week to use for time alignment during aggregation. The day must be in uppercase.
Integer hour
The hour of day to use for time alignment during aggregation.
String attributeName
The item_id, dimension name, IM name, or timestamp that you are modifying.
String attributeValue
The value that is applied for the chosen Condition.
String condition
The condition to apply. Valid values are EQUALS, NOT_EQUALS, LESS_THAN and
GREATER_THAN.
DataSource dataSource
Schema schema
String format
The format of the data, either CSV or PARQUET.
TimeSeriesIdentifiers timeSeriesIdentifiers
Details about the import file that contains the time series for which you want to create forecasts.
Action action
An array of actions that define a time series and how it is transformed. These transformations create a new time series that is used for the what-if analysis.
List<E> timeSeriesConditions
An array of conditions that define which members of the related time series are transformed.
Double quantile
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.
Double lossValue
The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.
String whatIfAnalysisArn
The Amazon Resource Name (ARN) of the what-if analysis.
String whatIfAnalysisName
The name of the what-if analysis.
String forecastArn
The Amazon Resource Name (ARN) of the baseline forecast that is being used in this what-if analysis.
String status
The status of the what-if analysis. 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 what-if analysis must be ACTIVE before you can access the analysis.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the what-if analysis was created.
Date lastModificationTime
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.
String whatIfForecastExportArn
The Amazon Resource Name (ARN) of the what-if forecast export.
List<E> whatIfForecastArns
An array of Amazon Resource Names (ARNs) that define the what-if forecasts included in the export.
String whatIfForecastExportName
The what-if forecast export name.
DataDestination destination
The path to the Amazon Simple Storage Service (Amazon S3) bucket where the forecast is exported.
String status
The status of the what-if forecast export. 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 what-if analysis must be ACTIVE before you can access the analysis.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the what-if forecast export was created.
Date lastModificationTime
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.
String whatIfForecastArn
The Amazon Resource Name (ARN) of the what-if forecast.
String whatIfForecastName
The name of the what-if forecast.
String whatIfAnalysisArn
The Amazon Resource Name (ARN) of the what-if analysis that contains this what-if forecast.
String status
The status of the what-if 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 what-if analysis must be ACTIVE before you can access the analysis.
String message
If an error occurred, an informational message about the error.
Date creationTime
When the what-if forecast was created.
Date lastModificationTime
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.
Date testWindowStart
The timestamp that defines the start of the window.
Date testWindowEnd
The timestamp that defines the end of the window.
Integer itemCount
The number of data points within the window.
String evaluationType
The type of evaluation.
SUMMARY - The average metrics across all windows.
COMPUTED - The metrics for the specified window.
Metrics metrics
Provides metrics used to evaluate the performance of a predictor.
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