/AWS1/CL_FCSDESCRPREDICTORRSP¶
DescribePredictorResponse
CONSTRUCTOR
¶
IMPORTING¶
Optional arguments:¶
IV_PREDICTORARN
TYPE /AWS1/FCSNAME
/AWS1/FCSNAME
¶
The ARN of the predictor.
IV_PREDICTORNAME
TYPE /AWS1/FCSNAME
/AWS1/FCSNAME
¶
The name of the predictor.
IV_ALGORITHMARN
TYPE /AWS1/FCSARN
/AWS1/FCSARN
¶
The Amazon Resource Name (ARN) of the algorithm used for model training.
IT_AUTOMLALGORITHMARNS
TYPE /AWS1/CL_FCSARNLIST_W=>TT_ARNLIST
TT_ARNLIST
¶
When
PerformAutoML
is specified, the ARN of the chosen algorithm.
IV_FORECASTHORIZON
TYPE /AWS1/FCSINTEGER
/AWS1/FCSINTEGER
¶
The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
IT_FORECASTTYPES
TYPE /AWS1/CL_FCSFORECASTTYPES_W=>TT_FORECASTTYPES
TT_FORECASTTYPES
¶
The forecast types used during predictor training. Default value is
["0.1","0.5","0.9"]
IV_PERFORMAUTOML
TYPE /AWS1/FCSBOOLEAN
/AWS1/FCSBOOLEAN
¶
Whether the predictor is set to perform AutoML.
IV_AUTOMLOVERRIDESTRATEGY
TYPE /AWS1/FCSAUTOMLOVERRIDESTRAG
/AWS1/FCSAUTOMLOVERRIDESTRAG
¶
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.
IV_PERFORMHPO
TYPE /AWS1/FCSBOOLEAN
/AWS1/FCSBOOLEAN
¶
Whether the predictor is set to perform hyperparameter optimization (HPO).
IT_TRAININGPARAMETERS
TYPE /AWS1/CL_FCSTRAININGPARAMS_W=>TT_TRAININGPARAMETERS
TT_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.
IO_EVALUATIONPARAMETERS
TYPE REF TO /AWS1/CL_FCSEVALPARAMETERS
/AWS1/CL_FCSEVALPARAMETERS
¶
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.
IO_HPOCONFIG
TYPE REF TO /AWS1/CL_FCSHYPPARAMTUNJOBCFG
/AWS1/CL_FCSHYPPARAMTUNJOBCFG
¶
The hyperparameter override values for the algorithm.
IO_INPUTDATACONFIG
TYPE REF TO /AWS1/CL_FCSINPUTDATACONFIG
/AWS1/CL_FCSINPUTDATACONFIG
¶
Describes the dataset group that contains the data to use to train the predictor.
IO_FEATURIZATIONCONFIG
TYPE REF TO /AWS1/CL_FCSFEATCONFIG
/AWS1/CL_FCSFEATCONFIG
¶
The featurization configuration.
IO_ENCRYPTIONCONFIG
TYPE REF TO /AWS1/CL_FCSENCRYPTIONCONFIG
/AWS1/CL_FCSENCRYPTIONCONFIG
¶
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
IO_PREDICTOREXECUTIONDETAILS
TYPE REF TO /AWS1/CL_FCSPREDICTOREXECDETS
/AWS1/CL_FCSPREDICTOREXECDETS
¶
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.
IV_ESTIMATEDTIMEREMAININGI00
TYPE /AWS1/FCSLONG
/AWS1/FCSLONG
¶
The estimated time remaining in minutes for the predictor training job to complete.
IV_ISAUTOPREDICTOR
TYPE /AWS1/FCSBOOLEAN
/AWS1/FCSBOOLEAN
¶
Whether the predictor was created with CreateAutoPredictor.
IT_DATASETIMPORTJOBARNS
TYPE /AWS1/CL_FCSARNLIST_W=>TT_ARNLIST
TT_ARNLIST
¶
An array of the ARNs of the dataset import jobs used to import training data for the predictor.
IV_STATUS
TYPE /AWS1/FCSSTATUS
/AWS1/FCSSTATUS
¶
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 beACTIVE
before you can use the predictor to create a forecast.
IV_MESSAGE
TYPE /AWS1/FCSMESSAGE
/AWS1/FCSMESSAGE
¶
If an error occurred, an informational message about the error.
IV_CREATIONTIME
TYPE /AWS1/FCSTIMESTAMP
/AWS1/FCSTIMESTAMP
¶
When the model training task was created.
IV_LASTMODIFICATIONTIME
TYPE /AWS1/FCSTIMESTAMP
/AWS1/FCSTIMESTAMP
¶
The last time the resource was modified. The timestamp depends on the status of the job:
CREATE_PENDING
- TheCreationTime
.
CREATE_IN_PROGRESS
- The current timestamp.
CREATE_STOPPING
- The current timestamp.
CREATE_STOPPED
- When the job stopped.
ACTIVE
orCREATE_FAILED
- When the job finished or failed.
IV_OPTIMIZATIONMETRIC
TYPE /AWS1/FCSOPTIMIZATIONMETRIC
/AWS1/FCSOPTIMIZATIONMETRIC
¶
The accuracy metric used to optimize the predictor.
Queryable Attributes¶
PredictorArn¶
The ARN of the predictor.
Accessible with the following methods¶
Method | Description |
---|---|
GET_PREDICTORARN() |
Getter for PREDICTORARN, with configurable default |
ASK_PREDICTORARN() |
Getter for PREDICTORARN w/ exceptions if field has no value |
HAS_PREDICTORARN() |
Determine if PREDICTORARN has a value |
PredictorName¶
The name of the predictor.
Accessible with the following methods¶
Method | Description |
---|---|
GET_PREDICTORNAME() |
Getter for PREDICTORNAME, with configurable default |
ASK_PREDICTORNAME() |
Getter for PREDICTORNAME w/ exceptions if field has no value |
HAS_PREDICTORNAME() |
Determine if PREDICTORNAME has a value |
AlgorithmArn¶
The Amazon Resource Name (ARN) of the algorithm used for model training.
Accessible with the following methods¶
Method | Description |
---|---|
GET_ALGORITHMARN() |
Getter for ALGORITHMARN, with configurable default |
ASK_ALGORITHMARN() |
Getter for ALGORITHMARN w/ exceptions if field has no value |
HAS_ALGORITHMARN() |
Determine if ALGORITHMARN has a value |
AutoMLAlgorithmArns¶
When
PerformAutoML
is specified, the ARN of the chosen algorithm.
Accessible with the following methods¶
Method | Description |
---|---|
GET_AUTOMLALGORITHMARNS() |
Getter for AUTOMLALGORITHMARNS, with configurable default |
ASK_AUTOMLALGORITHMARNS() |
Getter for AUTOMLALGORITHMARNS w/ exceptions if field has no |
HAS_AUTOMLALGORITHMARNS() |
Determine if AUTOMLALGORITHMARNS has a value |
ForecastHorizon¶
The number of time-steps of the forecast. The forecast horizon is also called the prediction length.
Accessible with the following methods¶
Method | Description |
---|---|
GET_FORECASTHORIZON() |
Getter for FORECASTHORIZON, with configurable default |
ASK_FORECASTHORIZON() |
Getter for FORECASTHORIZON w/ exceptions if field has no val |
HAS_FORECASTHORIZON() |
Determine if FORECASTHORIZON has a value |
ForecastTypes¶
The forecast types used during predictor training. Default value is
["0.1","0.5","0.9"]
Accessible with the following methods¶
Method | Description |
---|---|
GET_FORECASTTYPES() |
Getter for FORECASTTYPES, with configurable default |
ASK_FORECASTTYPES() |
Getter for FORECASTTYPES w/ exceptions if field has no value |
HAS_FORECASTTYPES() |
Determine if FORECASTTYPES has a value |
PerformAutoML¶
Whether the predictor is set to perform AutoML.
Accessible with the following methods¶
Method | Description |
---|---|
GET_PERFORMAUTOML() |
Getter for PERFORMAUTOML, with configurable default |
ASK_PERFORMAUTOML() |
Getter for PERFORMAUTOML w/ exceptions if field has no value |
HAS_PERFORMAUTOML() |
Determine if PERFORMAUTOML has a value |
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.
Accessible with the following methods¶
Method | Description |
---|---|
GET_AUTOMLOVERRIDESTRATEGY() |
Getter for AUTOMLOVERRIDESTRATEGY, with configurable default |
ASK_AUTOMLOVERRIDESTRATEGY() |
Getter for AUTOMLOVERRIDESTRATEGY w/ exceptions if field has |
HAS_AUTOMLOVERRIDESTRATEGY() |
Determine if AUTOMLOVERRIDESTRATEGY has a value |
PerformHPO¶
Whether the predictor is set to perform hyperparameter optimization (HPO).
Accessible with the following methods¶
Method | Description |
---|---|
GET_PERFORMHPO() |
Getter for PERFORMHPO, with configurable default |
ASK_PERFORMHPO() |
Getter for PERFORMHPO w/ exceptions if field has no value |
HAS_PERFORMHPO() |
Determine if PERFORMHPO has a value |
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.
Accessible with the following methods¶
Method | Description |
---|---|
GET_TRAININGPARAMETERS() |
Getter for TRAININGPARAMETERS, with configurable default |
ASK_TRAININGPARAMETERS() |
Getter for TRAININGPARAMETERS w/ exceptions if field has no |
HAS_TRAININGPARAMETERS() |
Determine if TRAININGPARAMETERS has a value |
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.
Accessible with the following methods¶
Method | Description |
---|---|
GET_EVALUATIONPARAMETERS() |
Getter for EVALUATIONPARAMETERS |
HPOConfig¶
The hyperparameter override values for the algorithm.
Accessible with the following methods¶
Method | Description |
---|---|
GET_HPOCONFIG() |
Getter for HPOCONFIG |
InputDataConfig¶
Describes the dataset group that contains the data to use to train the predictor.
Accessible with the following methods¶
Method | Description |
---|---|
GET_INPUTDATACONFIG() |
Getter for INPUTDATACONFIG |
FeaturizationConfig¶
The featurization configuration.
Accessible with the following methods¶
Method | Description |
---|---|
GET_FEATURIZATIONCONFIG() |
Getter for FEATURIZATIONCONFIG |
EncryptionConfig¶
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key.
Accessible with the following methods¶
Method | Description |
---|---|
GET_ENCRYPTIONCONFIG() |
Getter for ENCRYPTIONCONFIG |
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.
Accessible with the following methods¶
Method | Description |
---|---|
GET_PREDICTOREXECDETAILS() |
Getter for PREDICTOREXECUTIONDETAILS |
EstimatedTimeRemainingInMinutes¶
The estimated time remaining in minutes for the predictor training job to complete.
Accessible with the following methods¶
Method | Description |
---|---|
GET_ESTIMATEDTIMEREMAINING00() |
Getter for ESTIMATEDTIMEREMAININGINMINS, with configurable d |
ASK_ESTIMATEDTIMEREMAINING00() |
Getter for ESTIMATEDTIMEREMAININGINMINS w/ exceptions if fie |
HAS_ESTIMATEDTIMEREMAINING00() |
Determine if ESTIMATEDTIMEREMAININGINMINS has a value |
IsAutoPredictor¶
Whether the predictor was created with CreateAutoPredictor.
Accessible with the following methods¶
Method | Description |
---|---|
GET_ISAUTOPREDICTOR() |
Getter for ISAUTOPREDICTOR, with configurable default |
ASK_ISAUTOPREDICTOR() |
Getter for ISAUTOPREDICTOR w/ exceptions if field has no val |
HAS_ISAUTOPREDICTOR() |
Determine if ISAUTOPREDICTOR has a value |
DatasetImportJobArns¶
An array of the ARNs of the dataset import jobs used to import training data for the predictor.
Accessible with the following methods¶
Method | Description |
---|---|
GET_DATASETIMPORTJOBARNS() |
Getter for DATASETIMPORTJOBARNS, with configurable default |
ASK_DATASETIMPORTJOBARNS() |
Getter for DATASETIMPORTJOBARNS w/ exceptions if field has n |
HAS_DATASETIMPORTJOBARNS() |
Determine if DATASETIMPORTJOBARNS has a value |
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 beACTIVE
before you can use the predictor to create a forecast.
Accessible with the following methods¶
Method | Description |
---|---|
GET_STATUS() |
Getter for STATUS, with configurable default |
ASK_STATUS() |
Getter for STATUS w/ exceptions if field has no value |
HAS_STATUS() |
Determine if STATUS has a value |
Message¶
If an error occurred, an informational message about the error.
Accessible with the following methods¶
Method | Description |
---|---|
GET_MESSAGE() |
Getter for MESSAGE, with configurable default |
ASK_MESSAGE() |
Getter for MESSAGE w/ exceptions if field has no value |
HAS_MESSAGE() |
Determine if MESSAGE has a value |
CreationTime¶
When the model training task was created.
Accessible with the following methods¶
Method | Description |
---|---|
GET_CREATIONTIME() |
Getter for CREATIONTIME, with configurable default |
ASK_CREATIONTIME() |
Getter for CREATIONTIME w/ exceptions if field has no value |
HAS_CREATIONTIME() |
Determine if CREATIONTIME has a value |
LastModificationTime¶
The last time the resource was modified. The timestamp depends on the status of the job:
CREATE_PENDING
- TheCreationTime
.
CREATE_IN_PROGRESS
- The current timestamp.
CREATE_STOPPING
- The current timestamp.
CREATE_STOPPED
- When the job stopped.
ACTIVE
orCREATE_FAILED
- When the job finished or failed.
Accessible with the following methods¶
Method | Description |
---|---|
GET_LASTMODIFICATIONTIME() |
Getter for LASTMODIFICATIONTIME, with configurable default |
ASK_LASTMODIFICATIONTIME() |
Getter for LASTMODIFICATIONTIME w/ exceptions if field has n |
HAS_LASTMODIFICATIONTIME() |
Determine if LASTMODIFICATIONTIME has a value |
OptimizationMetric¶
The accuracy metric used to optimize the predictor.
Accessible with the following methods¶
Method | Description |
---|---|
GET_OPTIMIZATIONMETRIC() |
Getter for OPTIMIZATIONMETRIC, with configurable default |
ASK_OPTIMIZATIONMETRIC() |
Getter for OPTIMIZATIONMETRIC w/ exceptions if field has no |
HAS_OPTIMIZATIONMETRIC() |
Determine if OPTIMIZATIONMETRIC has a value |