In our company, we have a problem where we need to predict which user/vendor is likely to login at a particular time.
We have lots of data about which user logs in at which time. The problem is we have about 30K users, and each user is identified by a code, of say 32 digits.
I understand that simple classification will not work well as there are just too many classes over which the prediction is to be done. Also, I can't really make it as a regression problem as there is no ordering of prediction values.
What can I do in such situation?
Even in ImageNet they had only 1000 classes I guess, so my problem is just severe or I am not aware of the technique to handle such problems.
Please suggest any ways to tackle this problem.