Empresas comerciales zombis ecuatorianas: Una clasificación mediante Machine Learning

Reinaldo Armas Herrera, Ángel Alexander Higuerey Gómez, Ángel Ramón Sabando García, Mikel Ugando Peñate, Elvia Rosalia Inga Llanez, Pierina D’Elia Dimichelle

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

Resumen

In this article, we have studied which Machine Learning methodology most accurately predicts the presence of zombie companies in the Ecuadorian commercial sector. To do this, data from these companies in the years 2019, 2020 and 2021 were used. The zombie variable was defined as a binary variable that took the value of one if the company had had negative equity in the previous three years, and zero in another. case. The results determined that the different Machine Learning methods are accurate when predicting zombie companies, although logistic regression yields the best results in terms of ROC curves in the years 2019 and 2020, with the rest of the methods not being very distant in terms of results. For the rest of the metrics, Random Forest is the best independent technique of the year studied.

Título traducido de la contribuciónEcuadorian zombie commercial companies: A classification using Machine Learning
Idioma originalEspañol
Páginas (desde-hasta)541-554
Número de páginas14
PublicaciónRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Volumen2024
N.ºE68
EstadoPublicada - 2024

Nota bibliográfica

Publisher Copyright:
© 2024, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.

Palabras clave

  • Commerce
  • Ecuador
  • Machine Learning
  • Zombie companies

Huella

Profundice en los temas de investigación de 'Empresas comerciales zombis ecuatorianas: Una clasificación mediante Machine Learning'. En conjunto forman una huella única.

Citar esto