LSTM Time-series classification - derived feature I have a time-series dataset and I want to derive a new feature based on a date column which I believe might improve my predictive model. The feature is if it's weekday or weekend.

I am not sure how to create this for modeling purposes. Do I represent it as a boolean function or a numerical one (1/0) or just add 2 new features (weekday, weekend) and represent them as 1 and nan?
Add two new features, dummy variables, that represent the presence or absence of weekend and weekdays. You can create the feature (weekend/weekday) and use one hot encoding to create the two new.