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https://github.com/asma-hachaichi/adult-income-prediction
This project focuses on predicting the income of individuals based on a diverse set of demographic and socio-economic features. Using the Adult Income dataset, I used a Random Forest model to address this classification task.
https://github.com/asma-hachaichi/adult-income-prediction
income-prediction machine-learning prediction random-forest streamlit
Last synced: 21 days ago
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This project focuses on predicting the income of individuals based on a diverse set of demographic and socio-economic features. Using the Adult Income dataset, I used a Random Forest model to address this classification task.
- Host: GitHub
- URL: https://github.com/asma-hachaichi/adult-income-prediction
- Owner: asma-hachaichi
- Created: 2024-02-03T14:50:15.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-10-23T19:19:03.000Z (2 months ago)
- Last Synced: 2024-10-24T05:01:01.122Z (2 months ago)
- Topics: income-prediction, machine-learning, prediction, random-forest, streamlit
- Language: Python
- Homepage:
- Size: 13.4 MB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Adult Income Prediction App
This Streamlit application predicts whether a person's income is <=50K or >50K based on various demographic factors.
## Overview
The app uses a RandomForestClassifier model trained on demographic data to predict income levels. Users can input their details through a user-friendly web interface, and the model will output a prediction for their income bracket.
## Features
- Predict income level based on personal information
- Easy-to-use web interface
- Input validation and user feedback
## How to Use
1. Enter your age.
2. Select your work class from the dropdown.
3. Enter your final weight (continuous).
4. Select your education level from the dropdown.
5. Enter your education number (continuous).
6. Select your marital status from the dropdown.
7. Select your occupation from the dropdown.
8. Select your relationship status from the dropdown.
9. Select your race from the dropdown.
10. Select your gender (Male/Female).
11. Enter your capital gain (continuous).
12. Enter your capital loss (continuous).
13. Enter your hours worked per week (continuous).
14. Select your country from the dropdown.
After filling out all the information, click the "Submit" button to see the prediction.
## Installation
To run this application on your local machine, you will need Python and Streamlit installed.
```
pip install streamlit
pip install pickle
pip install pandas
```
After installing the necessary packages, you can start the app by running:
```
python -m streamlit run app.py
```
## Interface
Explore the Adult Income Prediction App's interface. Below is a snapshot of App in action:
## Contributions
Contributions are welcome. Please fork the project and submit a pull request.
## License
This project is licensed under the MIT License - see the LICENSE.md file for details.