Publications

  • Bertini Jr. J. R.; Graph embedded rules for explainable predictions in data streams, Neural Networks, p. 174-192, 2020.
  • Bertini Jr. J. R.; Nicoletti, M. C. An iterative boosting-based ensemble for streaming data classification. Information Fusion, p. 66-79, 2019.
  • Bertini Jr., J. R.; Nicoletti, M. C. ; Zhao, L. Attribute-based Decision Graphs: A framework for multiclass data classification. Neural Networks, v. 85, p. 69-84, 2017.
  • Bertini Jr., J. R.; Nicoletti, M. C. Enhancing classification performance using attribute-oriented functionally expanded data. Pattern Recognition Letters, v. 89, p. 39-45, 2017.
  • Bertini Jr., J. R.; Nicoletti, M. C.; Zhao, L. . An embedded imputation method via Attribute-based Decision Graphs. Expert Systems with Applications, v. 57, p. 159-177, 2016.
  • Bertini Jr., J. R.; Zhao, Liang; Lopes, A. A. An incremental learning algorithm based on the K-associated graph for non-stationary data classification. Information Sciences, v. 246, p. 52-68, 2013.
  • Bertini Jr., J. R.; L. Zhao; R. Motta; A. Lopes; Nonparametric classification method based on K-associated graphs. Information Sciences, v. 181, p. 5435-5456, 2011.
  • Bertini Jr., J. R.; Nicoletti, M. C. Attribute-Based Decision Graphs and Their Roles in Machine Learning Related Tasks. Intelligent Systems Reference Library. 1ed.: Springer International Publishing, 2018, v. , p. 53-71.
  • Bertini Jr., J. R.; Kasahara, V. A.; Nicoletti, M. C. . Approaching miRNA Family Classification Through Constructive Neural Networks. In: World Congress on Computational Intelligence, 2018, Rio de Janeiro. International Joint Conference on Neural Networks, 2018. p. 4280-4287.
  • Bertini Jr., J.R.; Nicoletti, M. C. A Genetic Algorithm for Improving the Induction of Attribute-based Decision Graph Classifiers. In: IEEE Congress on Evolutionary Computation (CEC), 2016, Vancouver. Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC), 2016. p. 4104-4110.

Full list of publications