References
- Yonghyuk Moon, Ikhee Shin, Yongju Shin, Okgi Min, "Recent Research & Development Trends in Automated Machine Learning," Electronics and Telecommunications Trends, Vol. 34 No. 4, pp. 32-42, Aug 1, 2019. https://dx.doi.org/10.22648/ETRI.2019.J.340404
- F. Hutter et al. (eds.), "Automated Machine Learning", The Springer Series on Challenges in Machine Learning, 2019, https://doi.org/10.1007/978-3-030-05318-5_1
- Hyperparameter Optimization, https://en.wikipedia.org/wiki/Hyperparameter_optimization.
- Claesen, Marc, and Bart De Moor. "Hyperparameter Search in Machine Learning", https://arxiv.org/abs/1502.02127
- Hyperparameter, https://en.wikipedia.org/wiki/Hyperparameter_(machine_learning).
- Scikit-learn, https://en.wikipedia.org/wiki/Scikit-learn.
- Scikit-learn, https://scikit-learn.org/.
- Tune, https://ray.readthedocs.io/en/latest/tune.html.
- Hyperopt, https://github.com/hyperopt/hyperopt.
- Auto-sklearn, https://github.com/automl/auto-sklearn.
- BOCS, https://github.com/baptistar/BOCS.
- mlrMBO, https://github.com/mlr-org/mlrMBO.
- scikit-optimize, https://github.com/scikit-optimize/scikit-optimize.
- FAR-HO, https://github.com/lucfra/FAR-HO.
- XGBoost, https://github.com/dmlc/xgboost.
- DEAP, https://github.com/DEAP/deap.
- DEvol, https://github.com/joeddav/devol.