This project aims to develop a predictive model for diabetes using the Random Forest algorithm and Flask framework. The model is trained on a dataset containing various health parameters and their corresponding diabetes outcomes.
- Utilizes Random Forest algorithm for accurate prediction
- Flask framework for building a user-friendly web application
- Interactive user interface for inputting health parameters
- Predicts the likelihood of diabetes based on the provided inputs
The dataset used for training the model is sourced from Kaggle and contains various health attributes, such as glucose level, blood pressure, BMI, and age, along with their corresponding diabetes outcomes.