shaowen1994/tamu_csce689_courseproject

Course project of CSCE689 (Graph Mining) in TAMU.

TAMU_CSCE689_CourseProject

Course project of CSCE689 (Graph Mining) in TAMU.

The data can be found in /Data/data.zip, and to run the code it need to be unzipped at first.

GAE / GVAE

Firstly build the conda environment with the file GVAE.yml in the /Emviroment folder.
Go to the folder /gae, and run the following command for training and validation, while version can be "gae" or "gvae":

python train_10FoldCV_gvae.py --m version

NeoDTI

Go to the folder /NeoDTI, and run the following command for training and validation:

python NeoDTI_cv.py

Graph Factorization

Go to the folder /gf, and run the command below for training and validation

python linkpre.py