https://github.com/fatimaafzaal/diabetes-prediction-project-using-voting-classifier

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.
https://github.com/fatimaafzaal/diabetes-prediction-project-using-voting-classifier

diabetes diabetes-prediction ensemble-learning ensemble-model jupyter-notebook machine-learning machine-learning-algorithms python voting votingclassifier

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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.

• Host: GitHub
• URL: https://github.com/fatimaafzaal/diabetes-prediction-project-using-voting-classifier
• Owner: fatimaAfzaal
• Created: 2023-09-08T03:41:19.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-09-19T14:03:20.000Z (about 1 year ago)
• Last Synced: 2024-01-29T11:24:07.722Z (10 months ago)
• Topics: diabetes, diabetes-prediction, ensemble-learning, ensemble-model, jupyter-notebook, machine-learning, machine-learning-algorithms, python, voting, votingclassifier
• Language: Jupyter Notebook
• Homepage:
• Size: 104 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Diabetes Prediction Project Using Voting Classifier

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.

## How to Use

1. Execute the provided Jupyter Notebook in your preferred environment.

2. Ensure you have the required dependencies installed.

3. Follow the step-by-step instructions in the notebook to explore the project.

4. Use the interactive interface to input your health attributes and obtain a diabetes prediction.

## Dependencies

- numpy

- pandas

- sklearn

- matplotlib

- seaborn

Feel free to contribute, provide feedback, or report issues related to this project.