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Installation

Mosaic ML relies on MCTS-based pipeline optimization library mosaic.

pip install git+https://github.com/herilalaina/mosaic@v0-alpha
pip install git+https://github.com/herilalaina/mosaic_ml

Example Mosaic ML Vanilla

A simple example of using mosaic to configure machine learning pipeline.

from mosaic_ml.automl import AutoML

X_train, y_train, X_test, y_test, cat = load_task(6)

autoML = AutoML(time_budget=120,
                time_limit_for_evaluation=100,
                memory_limit=3024,
                seed=1,
                scoring_func="balanced_accuracy",
                exec_dir="execution_dir"
                )

best_config, best_score = autoML.fit(X_train, y_train, X_test, y_test, categorical_features=cat)
print(autoML.get_run_history())

Initialization of Mosaic ML with Metalearning

Citation

@inproceedings{ijcai2019-457,
  title     = {Automated Machine Learning with Monte-Carlo Tree Search},
  author    = {Rakotoarison, Herilalaina and Schoenauer, Marc and Sebag, Michèle},
  booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on
               Artificial Intelligence, {IJCAI-19}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},             
  pages     = {3296--3303},
  year      = {2019},
  month     = {7},
  doi       = {10.24963/ijcai.2019/457},
  url       = {https://doi.org/10.24963/ijcai.2019/457},
}