AutoMLJobConfig
A collection of settings used for an AutoML job.
Contents
- CandidateGenerationConfig
-
The configuration for generating a candidate for an AutoML job (optional).
Type: AutoMLCandidateGenerationConfig object
Required: No
- CompletionCriteria
-
How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
Type: AutoMLJobCompletionCriteria object
Required: No
- DataSplitConfig
-
The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
Type: AutoMLDataSplitConfig object
Required: No
- Mode
-
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting
AUTO. InAUTOmode, Autopilot choosesENSEMBLINGfor datasets smaller than 100 MB, andHYPERPARAMETER_TUNINGfor larger ones.The
ENSEMBLINGmode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported byENSEMBLINGmode.The
HYPERPARAMETER_TUNING(HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported byHYPERPARAMETER_TUNINGmode.Type: String
Valid Values:
AUTO | ENSEMBLING | HYPERPARAMETER_TUNINGRequired: No
- SecurityConfig
-
The security configuration for traffic encryption or Amazon VPC settings.
Type: AutoMLSecurityConfig object
Required: No
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following:
