Ensemble of machine learning applied to economic cycles analysis: A comparative study using antecedent macroeconomic indicators for brazilian gdp prediction classification

• Palhares Junior, Eduardo ^[1] ; Araujo, Antonio Marcos Teixeira de ^[2] ; Souza, Adriano Honorato de ^[1] ; Silva, Noam Gadelha da ^[1] ; Souza, Wenndisson da Silva ^[2]
  1. [1] Intituto Federal do Amazonas, Itacoatiara, Amazonas.
  2. [2] Intituto Federal do Amazonas, Manaus, Amazonas.
• Localización: Revista Brasileira de Planejamento e Desenvolvimento, ISSN-e 2317-2363, Vol. 14, Nº. 2, 2025
• Idioma: portugués
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• Resumen

  • This work proposes a comparative study between several machine learning techniques, applied in the analysis of the phases of the Brazilian economic cycle. To this end, several macroeconomic indicators were used to build a model that was able to identify and predict the turning points of the economic cycle, such as the beginning of a recession or a recovery. The discretization of the variables proved to be decisive in the quality of the classification process, due to the diversity of the data and the non-linear nature of the analyzed phenomenon. The different techniques used reinforce a dilemma, because usually the best results come from very abstract methods, making it difficult to interpret the steps and their causes.