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guava-bandit t1_j62mxs8 wrote

For the separate columns question: depending on the importance that those in isolation would have on whether a customer would buy a product or not, you might want a feature per action and each with a flag value on whether the user did it or not. This is more something you’ll have to think about and to test out. If you do end up doing a feature per action, you might want to look at some regularisation for your logistic regression parameters, as maybe some of the actions are not as useful in predicting a good outcome.

For the training bit (.fit()), you need to pass in to the fit function your prepared dataset X used for training in 2D format and then for the y argument you need to pass in your class target data. I must say that the error you get confuses me a bit though.

I hope this is giving you some pointers though, and opening up the discussion to more useful input :)

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Thanos_nap OP t1_j62yrcn wrote

Yes, this is helpful. Thank you.

So to give you a idea of the actions, it has actions from our end and customer action (for marketing): Email / SMS / etc communication from our end Email open/sms clicked by customer

Transaction data actions: Bought x on date and time, bought y on date and time, etc.

All of it is arranged as per the timestamp of that action.

.fit() part I'm passing the data in same manner as you mentioned but not sure why the error is still there. Will check the tutorial someone else has posted!

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vwings t1_j63c9z7 wrote

Yes, good point. I would recommend to use KERAS for this modeling task. As soon as you have the data in the right data structure, you can solve this with maybe 25 lines of code ...

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