Creates an Amazon Forecast predictor.
Amazon Forecast creates predictors with AutoPredictor, which involves applying the optimal combination of algorithms to each time series in your datasets. You can use CreateAutoPredictor to create new predictors or upgrade/retrain existing predictors.
Creating new predictors
The following parameters are required when creating a new predictor:
PredictorName
- A unique name for the predictor.
DatasetGroupArn
- The ARN of the dataset group used to train the predictor.
ForecastFrequency
- The granularity of your forecasts (hourly, daily, weekly, etc).
ForecastHorizon
- The number of time steps being forecasted.
When creating a new predictor, do not specify a value for ReferencePredictorArn
.
Upgrading and retraining predictors
The following parameters are required when retraining or upgrading a predictor:
PredictorName
- A unique name for the predictor.
ReferencePredictorArn
- The ARN of the predictor to retrain or upgrade.
When upgrading or retraining a predictor, only specify values for the ReferencePredictorArn
and PredictorName
.
See also: AWS API Documentation
See ‘aws help’ for descriptions of global parameters.
create-auto-predictor
--predictor-name <value>
[--forecast-horizon <value>]
[--forecast-types <value>]
[--forecast-dimensions <value>]
[--forecast-frequency <value>]
[--data-config <value>]
[--encryption-config <value>]
[--reference-predictor-arn <value>]
[--optimization-metric <value>]
[--explain-predictor | --no-explain-predictor]
[--tags <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
--predictor-name
(string)
A unique name for the predictor
--forecast-horizon
(integer)
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length.
--forecast-types
(list)
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
.(string)
Syntax:
"string" "string" ...
--forecast-dimensions
(list)
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 specifystore_id
as a dimension to group sales forecasts for each store.(string)
Syntax:
"string" "string" ...
--forecast-frequency
(string)
The frequency of predictions in a forecast.
Valid intervals are Y (Year), M (Month), W (Week), D (Day), H (Hour), 30min (30 minutes), 15min (15 minutes), 10min (10 minutes), 5min (5 minutes), and 1min (1 minute). For example, “Y” indicates every year and “5min” indicates every five minutes.
The frequency must be greater than or equal to the TARGET_TIME_SERIES dataset frequency.
When a RELATED_TIME_SERIES dataset is provided, the frequency must be equal to the RELATED_TIME_SERIES dataset frequency.
--data-config
(structure)
The data configuration for your dataset group and any additional datasets.
DatasetGroupArn -> (string)
The ARN of the dataset group used to train the predictor.
AttributeConfigs -> (list)
Aggregation and filling options for attributes in your dataset group.
(structure)
Provides information about the method used to transform attributes.
The following is an example using the RETAIL domain:
{
"AttributeName": "demand",
"Transformations": {"aggregation": "sum", "middlefill": "zero", "backfill": "zero"}
}
AttributeName -> (string)
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
.Transformations -> (map)
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"
.key -> (string)
value -> (string)
AdditionalDatasets -> (list)
Additional built-in datasets like Holidays and the Weather Index.
(structure)
Describes an additional dataset. This object is part of the DataConfig object. Forecast supports the Weather Index and Holidays additional datasets.
Weather Index
The Amazon Forecast Weather Index is a built-in dataset that incorporates historical and projected weather information into your model. The Weather Index supplements your datasets with over two years of historical weather data and up to 14 days of projected weather data. For more information, see Amazon Forecast Weather Index .
Holidays
Holidays is a built-in dataset that incorporates national holiday information into your model. It provides native support for the holiday calendars of 66 countries. To view the holiday calendars, refer to the Jollyday library. For more information, see Holidays Featurization .
Name -> (string)
The name of the additional dataset. Valid names:
"holiday"
and"weather"
.Configuration -> (map)
Weather Index
To enable the Weather Index, do not specify a value for
Configuration
.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
key -> (string)
value -> (list)
(string)
JSON Syntax:
{
"DatasetGroupArn": "string",
"AttributeConfigs": [
{
"AttributeName": "string",
"Transformations": {"string": "string"
...}
}
...
],
"AdditionalDatasets": [
{
"Name": "string",
"Configuration": {"string": ["string", ...]
...}
}
...
]
}
--encryption-config
(structure)
An AWS Key Management Service (KMS) key and an AWS Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key. You can specify this optional object in the CreateDataset and CreatePredictor requests.
RoleArn -> (string)
The ARN of the IAM role that Amazon Forecast can assume to access the AWS KMS key.
Passing a role across AWS accounts is not allowed. If you pass a role that isn’t in your account, you get an
InvalidInputException
error.KMSKeyArn -> (string)
The Amazon Resource Name (ARN) of the KMS key.
Shorthand Syntax:
RoleArn=string,KMSKeyArn=string
JSON Syntax:
{
"RoleArn": "string",
"KMSKeyArn": "string"
}
--reference-predictor-arn
(string)
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
andPredictorName
. The value forPredictorName
must be a unique predictor name.
--optimization-metric
(string)
The accuracy metric used to optimize the predictor.
Possible values:
WAPE
RMSE
AverageWeightedQuantileLoss
MASE
MAPE
--explain-predictor
| --no-explain-predictor
(boolean)
Create an Explainability resource for the predictor.
--tags
(list)
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:
orAWS:
. Values can have this prefix. If a tag value hasaws
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 ofaws
do not count against your tags per resource limit. You cannot edit or delete tag keys with this prefix.(structure)
The optional metadata that you apply to a resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.
The following basic restrictions apply to tags:
Maximum number of tags per resource - 50.
For each resource, each tag key must be unique, and each tag key can have only one value.
Maximum key length - 128 Unicode characters in UTF-8.
Maximum value length - 256 Unicode characters in UTF-8.
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
Tag keys and values are case sensitive.
Do not use
aws:
,AWS:
, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value hasaws
as its prefix but the key does not, then Forecast considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix ofaws
do not count against your tags per resource limit.Key -> (string)
One part of a key-value pair that makes up a tag. A
key
is a general label that acts like a category for more specific tag values.Value -> (string)
The optional part of a key-value pair that makes up a tag. A
value
acts as a descriptor within a tag category (key).
Shorthand Syntax:
Key=string,Value=string ...
JSON Syntax:
[
{
"Key": "string",
"Value": "string"
}
...
]
--cli-input-json
| --cli-input-yaml
(string)
Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton
. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml
.
--generate-cli-skeleton
(string)
Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input
, prints a sample input JSON that can be used as an argument for --cli-input-json
. Similarly, if provided yaml-input
it will print a sample input YAML that can be used with --cli-input-yaml
. If provided with the value output
, it validates the command inputs and returns a sample output JSON for that command.
See ‘aws help’ for descriptions of global parameters.