This project focuses on predicting the likelihood of a person having diabetes based on various health-related attributes. It employs a Voting Classifier, which combines the predictions of multiple machine learning models, to improve prediction accuracy. Multiple machine learning models have been selected, including:
- Random Forest Classifier
- Logistic Regression
- Support Vector Machine (SVM)
These models have been combined using a Voting Classifier with a "soft" voting strategy to create an ensemble. The ensemble aims to improve prediction accuracy.
- Execute the provided Jupyter Notebook in your preferred environment.
- Ensure you have the required dependencies installed.
- Follow the step-by-step instructions in the notebook to explore the project.
- Use the interactive interface to input your health attributes and obtain a diabetes prediction.
- numpy
- pandas
- sklearn
- matplotlib
- seaborn
Feel free to contribute, provide feedback, or report issues related to this project.