Hi. First of all, I am very impressed of your implementation of NNMF model.
You said, in the SVINNMF paper, that the RMSE result of NNMF model on ML-100K is 0.9380. Right?
But, in my experiments, I achieve the RMSE 0.906 on that data. This result is consistent with the original NNMF paper's claim.
I think that you should you RMSPropOptimizer with learning rate 1e-3 and full batch including bias on MLP(I think that you're aware of this issue seeing the fix branch on this repository). I think these will leads you to enhance performance of your NNMF implementation.
I already uploaded my implementation. If you interested in this issue, please check my commit d63e7b134f24fff59baa90fb0cbf96befe8d479e in my NNMF repository and feel free to contact me. Thanks 👍
p.s. I really appreciated of your efforts on implementing NNMF model.
Hi. First of all, I am very impressed of your implementation of NNMF model. You said, in the SVINNMF paper, that the RMSE result of NNMF model on ML-100K is 0.9380. Right? But, in my experiments, I achieve the RMSE 0.906 on that data. This result is consistent with the original NNMF paper's claim. I think that you should you RMSPropOptimizer with learning rate 1e-3 and full batch including bias on MLP(I think that you're aware of this issue seeing the
fix
branch on this repository). I think these will leads you to enhance performance of your NNMF implementation. I already uploaded my implementation. If you interested in this issue, please check my commit d63e7b134f24fff59baa90fb0cbf96befe8d479e in my NNMF repository and feel free to contact me. Thanks 👍p.s. I really appreciated of your efforts on implementing NNMF model.