Enhancing Accuracy in Obesity Prediction and Nutrition Guidance through KNN and Decision Tree Models

Obesity remains defined as having too much body mass. This research aims to advance the precision of obesity prediction and refine nutrition guidance by using advanced machine learning techniques, specifically K-Nearest Neighbors (KNN) and Decision Tree models. In an era where lifestyle-related health concerns are on the rise, the significance of accurate obesity prediction and tailored nutritional advice cannot be overstated. This study explores the complex interactions between multiple factors that contribute to obesity, utilizing KNN and Decision Tree algorithms to improve prediction accuracy.