https://github.com/fatimaafzaal/diabetes-prediction-project-using-random-forest

This project focuses on predicting the likelihood of a person having diabetes based on various health-related attributes using Random Forest Algorithm
https://github.com/fatimaafzaal/diabetes-prediction-project-using-random-forest

colab-notebook ensemble-classifier ensemble-learning ensemble-machine-learning ensemble-model machine-learning machine-learning-algorithms python random-forest

Last synced: 1 day ago
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This project focuses on predicting the likelihood of a person having diabetes based on various health-related attributes using Random Forest Algorithm

• Host: GitHub
• URL: https://github.com/fatimaafzaal/diabetes-prediction-project-using-random-forest
• Owner: fatimaAfzaal
• Created: 2023-09-08T03:34:04.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-09-26T14:12:25.000Z (about 1 year ago)
• Last Synced: 2024-01-29T11:24:48.499Z (10 months ago)
• Topics: colab-notebook, ensemble-classifier, ensemble-learning, ensemble-machine-learning, ensemble-model, machine-learning, machine-learning-algorithms, python, random-forest
• 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 Random Forest

This project focuses on predicting the likelihood of a person having diabetes based on various health-related attributes. It utilizes the Random Forest classification algorithm to make predictions and provides a user-friendly interface for input and prediction.

## How to Use in Google Colab

1. Open the provided Jupyter Notebook in Google Colab.

2. Ensure you have the required dependencies installed within your Colab environment.

3. Execute the notebook cells in sequence, following the step-by-step instructions.

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.