/** * Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. * SPDX-License-Identifier: Apache-2.0. */ #pragma once #include #include #include #include namespace Aws { namespace Utils { namespace Json { class JsonValue; class JsonView; } // namespace Json } // namespace Utils namespace SageMaker { namespace Model { /** *

The collection of algorithms run on a dataset for training the model * candidates of an Autopilot job.

See Also:

AWS * API Reference

*/ class AutoMLAlgorithmConfig { public: AWS_SAGEMAKER_API AutoMLAlgorithmConfig(); AWS_SAGEMAKER_API AutoMLAlgorithmConfig(Aws::Utils::Json::JsonView jsonValue); AWS_SAGEMAKER_API AutoMLAlgorithmConfig& operator=(Aws::Utils::Json::JsonView jsonValue); AWS_SAGEMAKER_API Aws::Utils::Json::JsonValue Jsonize() const; /** *

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"

*/ inline const Aws::Vector& GetAutoMLAlgorithms() const{ return m_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"

*/ inline bool AutoMLAlgorithmsHasBeenSet() const { return m_autoMLAlgorithmsHasBeenSet; } /** *

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"

*/ inline void SetAutoMLAlgorithms(const Aws::Vector& value) { m_autoMLAlgorithmsHasBeenSet = true; m_autoMLAlgorithms = value; } /** *

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"

*/ inline void SetAutoMLAlgorithms(Aws::Vector&& value) { m_autoMLAlgorithmsHasBeenSet = true; m_autoMLAlgorithms = std::move(value); } /** *

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"

*/ inline AutoMLAlgorithmConfig& WithAutoMLAlgorithms(const Aws::Vector& value) { SetAutoMLAlgorithms(value); return *this;} /** *

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"

*/ inline AutoMLAlgorithmConfig& WithAutoMLAlgorithms(Aws::Vector&& value) { SetAutoMLAlgorithms(std::move(value)); return *this;} /** *

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"

*/ inline AutoMLAlgorithmConfig& AddAutoMLAlgorithms(const AutoMLAlgorithm& value) { m_autoMLAlgorithmsHasBeenSet = true; m_autoMLAlgorithms.push_back(value); return *this; } /** *

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"

*/ inline AutoMLAlgorithmConfig& AddAutoMLAlgorithms(AutoMLAlgorithm&& value) { m_autoMLAlgorithmsHasBeenSet = true; m_autoMLAlgorithms.push_back(std::move(value)); return *this; } private: Aws::Vector m_autoMLAlgorithms; bool m_autoMLAlgorithmsHasBeenSet = false; }; } // namespace Model } // namespace SageMaker } // namespace Aws