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Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution

, , , и . Arxiv Preprint, (11.06.2022)
DOI: 10.48550/arXiv.2206.05447

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Giuseppe Olivato

Giuseppe Veltri

Giuseppe Amato

Giuseppe Rossi

Giuseppe Bosco

 

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Developing Open Source Educational Resources for Machine Learning and Data Science., , , , , , и . Teaching ML, том 207 из Proceedings of Machine Learning Research, стр. 1-6. PMLR, (2022)On benchmark experiments and visualization methods for the evaluation and interpretation of machine learning models.. Ludwig Maximilian University of Munich, Germany, (2019)Interpretable Regional Descriptors: Hyperbox-Based Local Explanations., , , и . ECML/PKDD (3), том 14171 из Lecture Notes in Computer Science, стр. 479-495. Springer, (2023)Efficient and Accurate Explanation Estimation with Distribution Compression., , , и . CoRR, (2024)On the Robustness of Global Feature Effect Explanations., , , и . ECML/PKDD (2), том 14942 из Lecture Notes in Computer Science, стр. 125-142. Springer, (2024)Towards Explaining Hyperparameter Optimization via Partial Dependence Plots, , , , и . Proceedings of the international workshop on Automated Machine Learning (AutoML) at ICML'21, (июля 2021)Enhancing Explainability of Hyperparameter Optimization via Bayesian Algorithm Execution, , , и . Arxiv Preprint, (11.06.2022)Developing Open Source Educational Resources for Machine Learning and Data Science., , , , , , и . CoRR, (2021)Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model Agnostic Interpretations., , , , и . CoRR, (2019)Algorithm-Agnostic Feature Attributions for Clustering., , и . xAI (1), том 1901 из Communications in Computer and Information Science, стр. 217-240. Springer, (2023)