Interface AutoMLAlgorithmConfig.Builder

All Superinterfaces:
Buildable, CopyableBuilder<AutoMLAlgorithmConfig.Builder,AutoMLAlgorithmConfig>, SdkBuilder<AutoMLAlgorithmConfig.Builder,AutoMLAlgorithmConfig>, SdkPojo
Enclosing class:
AutoMLAlgorithmConfig

public static interface AutoMLAlgorithmConfig.Builder extends SdkPojo, CopyableBuilder<AutoMLAlgorithmConfig.Builder,AutoMLAlgorithmConfig>
  • Method Details

    • autoMLAlgorithmsWithStrings

      AutoMLAlgorithmConfig.Builder autoMLAlgorithmsWithStrings(Collection<String> autoMLAlgorithms)

      The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.

      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"

      Parameters:
      autoMLAlgorithms - The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.

      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"

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • autoMLAlgorithmsWithStrings

      AutoMLAlgorithmConfig.Builder autoMLAlgorithmsWithStrings(String... autoMLAlgorithms)

      The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.

      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"

      Parameters:
      autoMLAlgorithms - The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.

      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"

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • autoMLAlgorithms

      AutoMLAlgorithmConfig.Builder autoMLAlgorithms(Collection<AutoMLAlgorithm> autoMLAlgorithms)

      The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.

      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"

      Parameters:
      autoMLAlgorithms - The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.

      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"

      Returns:
      Returns a reference to this object so that method calls can be chained together.
    • autoMLAlgorithms

      AutoMLAlgorithmConfig.Builder autoMLAlgorithms(AutoMLAlgorithm... autoMLAlgorithms)

      The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.

      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"

      Parameters:
      autoMLAlgorithms - The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.

      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"

      Returns:
      Returns a reference to this object so that method calls can be chained together.