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teenaxta t1_j62mz4o wrote

Customer ID is useless so obviously it will be dropped. Now the actions he did is a bit tricky.

if actions are discrete classes, then i think you should break up the column into sub classes and then one hot encode the actions.

I cant really understand why you need LSTM here. Do you have a sequence data or any sort of temporal component ? If you have to use LSTM you can just set your sequence length to 1 and essentially use it as a NN. But that makes no sense honestly. Would be much better to use something like XGboost

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Thanos_nap OP t1_j62nsnj wrote

Oh yes customer ID will be dropped that was just for identification. As for why we need LSTM..that's because they just want it with LSTM because LSTM is the "new" thing here. That's all..i have explained them it's not really needed but obviously top management knows better.

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vwings t1_j63c23v wrote

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..

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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!

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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....

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vwings t1_j63c3ss wrote

How do you know that the costumer is male?

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