/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.

Primary LanguageJupyter Notebook

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.