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A Large-Scale Study of Hyperparameter Tuning for Machine Learning Algorithms.

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High Per Parameter

Code accompanying the paper: M. Sipper, "High Per Parameter: A Large-Scale Study of Hyperparameter Tuning for Machine Learning Algorithms", Algorithms 2022, 15, 315.

  • main.py: main module (Algorithm 1 in the paper)
  • datasets.py: handle datasets used
  • tune.py: hyperparameter tuning with Optuna
  • score.py: compute metrics
  • hp.py: define hyperparamter ranges/sets per algorithm
  • stats.py: compute stats and hp_score

Citation

Citations are always appreciated 😊:

@Article{Sipper2022Hyper,
AUTHOR = {Sipper, Moshe},
TITLE = {High Per Parameter: A Large-Scale Study of Hyperparameter Tuning for Machine Learning Algorithms},
JOURNAL = {Algorithms},
VOLUME = {15},
YEAR = {2022},
NUMBER = {9},
ARTICLE-NUMBER = {315},
}

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