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 :)
guava-bandit t1_j62mxs8 wrote
Reply to [P] Building a LSTM based model for binary classification by Thanos_nap
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 :)