Create virtualenv with

$ virtualenv -p python3 venv

Activate it and install depenencies

$ . ./env.sh  or $ . ./venv/bin/activate
$ pip install -r requirements.txt

Download the data from:

Link

Alternatively:

$ kaggle competitions download -c link-prediction-data-challenge-2019

Whenever you install something new, add it with

$ pip freeze > requirements.txt

Install the necassary libraries.

• Original data files are expected in the main directory.

Files/folders:

• Preprocessing.ipynb preprocessing of text data to create created stemmed corpus. Must be run first.
• INF554_Simple.ipynb run after Preprocessing.ipynb, calculates the main graph and text based features.
• INF554_Node2Vec.ipynb run after INF554_Simple.ipynb, calculated node2vec embeddings.
• INF554_Ensemble.ipynb run last. This file created various models and combined their results in a model ensemble to improve performance.
• ./pickles stored the pickles features.