Prediction of the level of obesity in people using the decision tree model

• Autores: Delgado Huacallo, Renato Eduardo, Ilachoque Hanccoccallo, Christian, Luque Sanabria, Felman, Paniura Huamani, Jose Maykol
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad La Salle
• Repositorio: Revistas - Universidad La Salle
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.ulasalle.edu.pe:article/71
• Enlace del recurso: https://revistas.ulasalle.edu.pe/innosoft/article/view/71; https://doi.org/10.48168/innosoft.s9.a71; https://purl.org/42411/s9/a71; https://n2t.net/ark:/42411/s9/a71
• Nivel de acceso: acceso abierto
• Materia: Obesity; decision tree; level of obesity; Obesidad; árbol de decisión; nivel de obesidad

Obesity is a public health problem that affects the world population, that is why the present work is oriented to present a computer solution for the estimation and prediction of obesity levels, making it possible for a person to know their current physical condition for this we used a dataset of people with obesity from different countries like Peru, Mexico and Colombia based on their eating habits and their physical condition, creating a decision tree with all these data.