Game Ratings Predictor

Hi everyone!
This is a project originally made by Roberto Falconi and Federico Guidi with Professor Luigi Freda for their course "Quantitative Methods for Computer Science", based at Sapienza - University of Rome.

The code is open source and written in Python 3.x but it's also Python 2.x backward compatible.

The program uses the Kaggle dataset available at https://www.kaggle.com/rush4ratio/video-game-sales-with-ratings and the Python libraries "Pandas" and "Sklearn".

This project goal is to classifie each video game in the dataset by ESRB rating, to do this we used Logistic Regression, Random Forest and k-NN.

How to run GameRatingsPredictor

Ubuntu, Debian and macOS users:

First of all, you need pip and Python installed. If you're on Ubuntu or Debian, make sure you have Python Developer installed with sudo apt-get install python-dev. If you're on macOS, it should be already installed with Python. Otherwise, consider reinstalling Python.

1. Upgrade pip to the latest version with pip install --upgrade pip.
2. Download the repository and open a terminal inside the root.
3. Run sudo pip install -r requirements.txt, it'll install all the required packages (about 88.4MB).
4. Now you have two options:
   1. Run sudo python setup.py install --record files.txt. Now you can run the whole project with the command line algoritmo anywhere in the terminal.
      You can uninstall it with cat files.txt | xargs rm -rf.
   2. Run the project with python algoritmo-runner.py without any installation.

You're done!

Windows users:

1. Go to https://www.python.org/downloads/windows/, download and run the .exe

2. Download the get-pip.py file from https://bootstrap.pypa.io/get-pip.py

3. Install it with (you might need an administrator command prompt to do this): python get-pip.py

4. Go to the directory where Python has been installed, now in the Scripts directory make a new file called local.bat with the only word cmd in it

5. Double click local.bat and in the just opened terminal write:

    pip install numpy
    pip install scipy
    pip install pandas
    pip install -U scikit-learn
   

6. Run algoritmo.py with Python IDLE or the IDE you prefer!