AutoMLAlgorithmConfig - Amazon SageMaker (original) (raw)

The selection of algorithms trained on your dataset to generate the model candidates for an Autopilot job.

Contents

AutoMLAlgorithms

The selection of algorithms trained on your dataset to generate the model candidates for an Autopilot job.

• For the tabular problem typeTabularJobConfig:

Note

Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (ENSEMBLING orHYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.

• In ENSEMBLING mode:
  * "catboost"
  * "extra-trees"
  * "fastai"
  * "lightgbm"
  * "linear-learner"
  * "nn-torch"
  * "randomforest"
  * "xgboost"
• In HYPERPARAMETER_TUNING mode:
  * "linear-learner"
  * "mlp"
  * "xgboost"
• For the time-series forecasting problem typeTimeSeriesForecastingJobConfig:
  • Choose your algorithms from this list.
    * "cnn-qr"
    * "deepar"
    * "prophet"
    * "arima"
    * "npts"
    * "ets"

Type: Array of strings

Array Members: Minimum number of 0 items. Maximum number of 11 items.

Valid Values: xgboost | linear-learner | mlp | lightgbm | catboost | randomforest | extra-trees | nn-torch | fastai | cnn-qr | deepar | prophet | npts | arima | ets

Required: Yes

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following:

• AWS SDK for C++
• AWS SDK for Java V2
• AWS SDK for Ruby V3

AthenaDatasetDefinition

AutoMLCandidate

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