Car Desirability Analysis

Python based Miniproject implementing KNN and Apriori Algorithm on "Car Evaluation Dataset"

Languages Used

1. Python (Backend)
2. HTML (Frontend)
3. CSS3 (Frontend)
4. JavaScript (Frontend)

Frameworks & Libraries Used:

1. Flask
2. Pandas
3. Numpy
4. Arules
5. Scikit-learn
6. Selenium

How to Setup:

1. Clone this repo
2. Open repo folder in Terminal/PS
3. Create virtual-env (Assuming Python3 installed) python -m venv venv
4. Activate virtual-env (Windows) .\venv\Scripts\activate or (Linux) . venv/bin/activate
5. Run pip install -r requirements.txt
6. Download: Arules and extract into venv\lib\site-packages\ (replace existing files).
7. Run python car_evaluation.py
8. The project will be available at localhost:5000

Selenium Testing:

1. For Selenium testing, you'll need Selenium Firefox driver: Geckodriver installed, and on PATH.
2. Alternately, you can use Selenium Chrome driver: ChromeDriver installed, and on PATH as well. In this case, you'll have to change code from webdriver.Firefox() to webdriver.Chrome().

Dataset

This project implements KKN to predict the Acceptability of a Car having input features based on model trained using the above dataset. It also briefs the factors leading to each of the decisions ( Unacceptable, Acceptable Good Preferred & VGood Optimal ) using Apriori Algorithm.