Placement Prediction

Developed by daniel-was-taken, VaishnaviSawant1901, PremTatkari, rachelabe01

Placement Prediction System analyzes the previous year's student's historical data and predicts placement chances of "current students”. Students having better chance of placement are given the message as higher chance, if not then lower chance. We decided to select three algorithms, namely KNN, Decision tree and Random Forest.

The jupyter notebook (placement_model.ipynb) shows the comparision of the various algorithms such as the KNN regression, Decision Tree, Random Forest and GaussianNB out of which, Decision Tree has a higher accuracy score than the other algorithms.

How to run:

1. Install venv on Windows by running: pip install virtualenv
2. Create virtualenv by running: virtualenv environmentname
3. Activate environment: environmentname\Scripts\activate
4. Install python packages: pip install -r requirements.txt
5. Run placement.py in VSCode by going to Run > Start Debugging OR simply pressing F5
6. Run app: flask --app app run

NOTE:

1. MySQL Workbench should be installed

Ref: https://www.w3schools.com/mysql/mysql_install_windows.asp

2. Setup database in MySQL

Ref: https://codeshack.io/login-system-python-flask-mysql/

From the above link make the following changes:

1. Database name from pythonlogin to login
2. Table name from accounts to auth
3. Column name from username to name