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This study presents an innovative approach to predicting obesity levels using explainable artificial intelligence (XAI) that focuses on lifestyle factors instead of traditional BMI measures. The best-performing machine learning model achieved 86.5% accuracy with the Random Forest algorithm, highlighting the significance of meal frequency and technology usage in obesity risk. The research emphasizes the potential of model-agnostic methods to uncover complex relationships between lifestyle factors and obesity

Author

Claudia Jocelyn Reyes Hernández

Language

EN