ArticleData in brief2019
Dataset for estimation of obesity levels based on eating habits and physical condition in individuals from Colombia, Peru and Mexico.
Article in Data in brief, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Lifestyle data-based multiclass obesity prediction with interpretable ensemble models incorporating SHAP and LIME analysis.Scientific reports · 2025Article
- Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence.Frontiers in physiology · 2025Article
- Functional partitioning through competitive learning.Frontiers in artificial intelligence · 2025Article
- Balancing misclassification errors in image-based inference using problem domain semantics and a nested cascade architecture.Neural computing & applications · 2025Article
- A lifestyle-based prediction model for obesity in Chinese adolescent students.Frontiers in sports and active living · 2025Article
- Unraveling the Potential of Attentive Bi-LSTM for Accurate Obesity Prognosis: Advancing Public Health towards Sustainable Cities.Bioengineering (Basel, Switzerland) · 2024Article
- Unveiling value patterns via deep reinforcement learning in heterogeneous data analytics.Patterns (New York, N.Y.) · 2024Article
- Affectation of COVID-19 pandemic on the use and abundance of wild resources in Tabasco, Mexico: A qualitative assessment.PloS one · 2024Article
- Prediction and classification of obesity risk based on a hybrid metaheuristic machine learning approach.Frontiers in big data · 2024Article
- Estimation of Obesity Levels through the Proposed Predictive Approach Based on Physical Activity and Nutritional Habits.Diagnostics (Basel, Switzerland) · 2023Article
- Hybrid Majority Voting: Prediction and Classification Model for Obesity.Diagnostics (Basel, Switzerland) · 2023Article
- Synthetic Tabular Data Evaluation in the Health Domain Covering Resemblance, Utility, and Privacy Dimensions.Methods of information in medicine · 2023Article
- Personalized optimal nutrition lifestyle for self obesity management using metaalgorithms.Scientific reports · 2022Article
- Fair Generalized Linear Models with a Convex Penalty.Proceedings of machine learning research · 2022Article
- The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation.PeerJ. Computer science · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents data for the estimation of obesity levels in individuals from the countries of Mexico, Peru and Colombia, based on their eating habits and physical condition. The data contains 17 attributes and 2111 records, the records are labeled with the class variable NObesity (Obesity Level), that allows classification of the data using the values of Insufficient Weight, Normal Weight, Overweight Level I, Overweight Level II, Obesity Type I, Obesity Type II and Obesity Type III. 77% of the data was generated synthetically using the Weka tool and the SMOTE filter, 23% of the data was collected directly from users through a web platform. This data can be used to generate intelligent computational tools to identify the obesity level of an individual and to build recommender systems that monitor obesity levels. For discussion and more information of the dataset creation, please refer to the full-length article "Obesity Level Estimation Software based on Decision Trees" (De-La-Hoz-Correa et al., 2019).
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