I have a large longitudinal dataset with 5 minute granularity for a period of around 30 months from thousands of households. I would like to classify them using a binary output (0/1) based on the input which is also a set of binary variables (sensors activated or not 0/1). I have a training dataset available with the labeled binary output (0/1) with binary inputs.
I would like to know which machine learning model will be best for this type of case where both input and outputs are binary in nature.
Whether Logistic regression is one of the options or not?