This project aims to build a machine learning model to predict whether a person is diabetic based on medical data such as blood glucose levels, BMI, and other health indicators. The goal is to create an efficient predictive system using a Support Vector Machine (SVM) model.
Diabetes is a chronic condition that affects millions of people worldwide. Early detection and management are crucial for preventing serious complications. This project uses a supervised machine learning approach to predict diabetes based on various health metrics.
Medical Data Input: Utilizes health indicators like glucose levels, BMI, insulin levels, etc. Support Vector Machine (SVM): The core machine learning algorithm used to classify diabetic and non-diabetic cases. Data Preprocessing: Includes steps like handling missing data, feature scaling, and data standardization. Model Evaluation: Assess the model’s accuracy on both training and testing datasets.
Feel free to submit issues, fork the repository, and send pull requests. Contributions are welcome!