I continued to preprocess the data and engineer relevant features. This included creating new variables to represent the combined effects of obesity and inactivity on diabetes risk. Feature engineering is essential for building more accurate predictive models.
Later I started developing machine learning models to predict diabetes risk based on inactivity levels. My preliminary models include linear regression. I am working on fine-tuning the model and plan to explore more complex algorithms in the coming weeks. Next, building on my initial EDA, I created more advanced visualizations to illustrate the relationships between obesity, inactivity, and diabetes. These visualizations will play a crucial role in communicating our findings.