mlns-project

Deep Learning based Graph embedding for nodes clustering Project for the Machine Learning in Network Science class at CentraleSupélec.

Structure of the repository

Non-deep algorithms

Non-deep algorithms including:

• KMeans
• Spectral Clustering
• RMSC are in the file clustering.py, with rather clean names. Can be launched with Python CLI to get the visualization results (can be a bit long).

VAEs

VAE and IWAE are in the file vae_clustering.py. Can be launched with Python CLI to get the visualization results (can be a bit long).

Visualization functions

In the file visualization.py.

DAEGC

This algorithm is seperated from the rest. You should go to the daegc directory:

cd daegc/

Then, to launch this algorithm, you should first pretrain the auto-encoder. For this you should run this command from the daegc folder:

python pretrain.py

To train the other algorithm, you can launch:

python training.py