Multi-Level Stacking

  • Fabiana Coutinho Boldrin USP
  • Adriano Henrique Cantão USP
  • Renato Tinós USP
  • José Augusto Baranauskas USP


Stacking é um dos algoritmos que combina os resultados de diferentes classificadores que foram gerados utilizando o mesmo conjunto de treinamento. Com objetivo de explorar alguns aspectos com relação ao algoritmo de stacking como o número de levels (camadas) de aprendizado, o número de classificadores por level e os algoritmos de utilizados, foi proposto o multi-level stacking. Para este trabalho foram feitos experimentos utilizando três tipos diferentes de indutores para diferentes datasets com dois levels de aprendizado.


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BOLDRIN, Fabiana Coutinho; CANTÃO, Adriano Henrique; TINÓS, Renato; BARANAUSKAS, José Augusto. Multi-Level Stacking. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 19. , 2022, Campinas/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 1-12. ISSN 2763-9061. DOI: