lyst/lightfm 1.12

on GitHub

Changed

• Ranks are now computed pessimistically: when two items are tied, the positive item is assumed to have higher rank. This will lead to zero precision scores for models that predict all zeros, for example.
• The model will raise a ValueError if, during fitting, any of the parameters become non-finite (NaN or +/- infinity).
• Added mid-epoch regularization when a lot of regularization is used. This reduces the likelihood of numerical instability at high regularization rates.