UCLA

The objective of this paper is to employ various machine learning algorithms to investigate the assessment of obesity levels based on eating habits and physical conditions. The study will utilize the obesity level estimation data provided by UCI Machine Learning Repository. The performance of different model candidates will be evaluated and compared in order toselect the most robust model for obesity estimation or prediction. Moreover, this research aims to identify the crucial features used in the best predictive model to enhance the accuracy of obesity prediction. This study intends to contribute to the ongoing research in the field of machine learning and healthcare by providing insights into the prediction of obesity.