You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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.