AutoMLAlgorithmConfig - Amazon SageMaker
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AutoMLAlgorithmConfig

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

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AutoMLAlgorithms

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

  • For the tabular problem type TabularJobConfig:

    Note

    Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (ENSEMBLING or HYPERPARAMETER_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 type TimeSeriesForecastingJobConfig:

    • 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: