GithubHelp home page GithubHelp logo

hlostam / ouroboros_paper Goto Github PK

View Code? Open in Web Editor NEW
3.0 3.0 2.0 3.23 MB

Code and experiments in vagrant for the Ouroboros prediction model for predicting at-risk students

Jupyter Notebook 93.95% Python 6.05%

ouroboros_paper's Introduction

Ouroboros experiments running

The experiments for the Ouroboros are written in Python3. For easy usage and reproducing the experiments Vagrant file was created. Using vagrant, new virtual machine (VM) will be installed with all the necessary source codes and libraries. This VM serves as the platform for the experiments.

Installation - Preparing of the experiment platform

Dependencies

  • VirtualBox
  • Vagrant
  1. Download and install virtualbox -- the VM image was created using virtualbox.

    https://www.virtualbox.org/wiki/Downloads

  2. Download and install vagrant:

    https://www.vagrantup.com/downloads.html

  3. Locate the Vagrant file and run

    vagrant up

    This operation might take some time as the virtual machine image is downloaded together with python libraries necessary for running the experiments.

Running the experiments

  1. Now open your browser on your operating system and enter url: http://localhost:8888/

  2. Jupyter notebook will show up with the list of notebooks that contain the experiments.

    • ouroboros_experiments.ipynb -- experiments from the evaluation part of the paper
    • ouroboros_stats.ipynb -- various statistic/summary information that were used for the introduction and motivation of the paper
  3. Open ouroboros_experiment.ipynb and click on Cell->Run All in the top menu

  4. Now all the experiments are run and the graphs are generated.

ouroboros_paper's People

Stargazers

 avatar  avatar  avatar

Watchers

 avatar Tao avatar  avatar

Forkers

qiujkx taozeze

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.