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Rethinking Defaults Values: a Low Cost and Efficient Strategy to Define Hyperparameters
Machine Learning (ML) algorithms have been successfully employed by a va...
07/31/2020 ∙ by Rafael Gomes Mantovani, et al. ∙
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Towards meta-learning for multi-target regression problems
Several multi-target regression methods were devel-oped in the last year...
07/25/2019 ∙ by Gabriel Jonas Aguiar, et al. ∙
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A meta-learning recommender system for hyperparameter tuning: predicting when tuning improves SVM classifiers
For many machine learning algorithms, predictive performance is critical...
06/04/2019 ∙ by Rafael Gomes Mantovani, et al. ∙
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An empirical study on hyperparameter tuning of decision trees
Machine learning algorithms often contain many hyperparameters whose val...
12/05/2018 ∙ by Rafael Gomes Mantovani, et al. ∙
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