Implementation of CFGAN. The implementation based on Pytorch is done, and the max precision on ML100k is 0.49 in 1000 train epochs, when use the paramaters in the paper.
cfgan.py : the model of CFGAN
data.py : load data
main.py : train and show result
Run the demo :
Python main.py
You can modify paramaters in main.py, for example, modify the alpha to 0.5(in fact, result turn better when you do that)
Next, we consider implementing another version based on Tensorflow.
Author: Xuxin Zhang, HUST, xuxinz@hust.edu.cn
Reference: Chae D K , Kang J S , Kim S W , et al. CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks[C]// the 27th ACM International Conference. ACM, 2018.
Baseline: https://github.com/1051003502/CFGAN