Viewing a single comment thread. View all comments

vwings t1_j63c23v wrote

Reply to comment by Thanos_nap in [P] Building a LSTM based model for binary classification by Thanos_nap

Lol, LSTM for the sake of it. If there is no temporal component, then it's just the wrong model. Can you tell them that Transformers are the "new" LSTMs? Transformers handle sets (instead of sequences), so they would make a lot of sense in your application..

2

Thanos_nap OP t1_j63dyc3 wrote

There is a temporaral component. These customer actions are week wise. So the data is Customer ID, week number, action, converted yes or no.

I can get this in the 3d shape with time step as week, features = actions. But I'm confused what would be the batch here.

But yes, i agree with you this is not the best method for my use case!

2

vwings t1_j64itph wrote

The batch dimensions are the different customers. You have N costumers, across T weeks and possible actions. This should give you a sparse tensor of dimensions [N,T,K] that you can easily plug into any LSTM....

2