Closed mokarakaya closed 5 years ago
It looks like your L2 regularization is very high. Can you try with a lower value?
Thanks for the quick reply.
Low L2 and high n_iter solved my issue; l2=1e-10, n_iter=100,
The loss starts to decrease after around 60th epoch. So, I think it was an underfitting problem.
I created the model as follows similar to the tests;
And I recommend items to all sequences in test_seq. There are 229 sequences. So, in the loop below, I recommend k * 229 items. However, all recommendations are same for any sequence in test_seq. In order words, len(aggregate_diversity) = k for losses = pointwise or bpr
adaptive_hinge works well.
I've tried k =10 and k =20 and got the same results. I've used Movielens 100K dataset.
Do I miss something?