no code implementations • 31 Jul 2020 • Rafael Gomes Mantovani, André Luis Debiaso Rossi, Edesio Alcobaça, Jadson Castro Gertrudes, Sylvio Barbon Junior, André Carlos Ponce de Leon Ferreira de Carvalho
Our approach is grounded on a small set of optimized values able to obtain predictive performance values better than default settings provided by popular tools.
no code implementations • 25 Jul 2019 • Gabriel Jonas Aguiar, Everton José Santana, Saulo Martiello Mastelini, Rafael Gomes Mantovani, Sylvio Barbon Jr
In this paper, we propose a meta-learning system to recommend the best predictive method for a given multi-target regression problem.
1 code implementation • 4 Jun 2019 • Rafael Gomes Mantovani, André Luis Debiaso Rossi, Edesio Alcobaça, Joaquin Vanschoren, André Carlos Ponce de Leon Ferreira de Carvalho
For many machine learning algorithms, predictive performance is critically affected by the hyperparameter values used to train them.
2 code implementations • 5 Dec 2018 • Rafael Gomes Mantovani, Tomáš Horváth, André L. D. Rossi, Ricardo Cerri, Sylvio Barbon Junior, Joaquin Vanschoren, André Carlos Ponce de Leon Ferreira de Carvalho
DT induction algorithms present high predictive performance and interpretable classification models, though many HPs need to be adjusted.