Modeling the influence of events order on probability The case is to model if the sequence of events influences the probability of binary target variable. We have for example five different events which occur in time (event: A,B,C,D,E). They can occur in order from 1 to 5. I would like to check if the order of their occurrence influences the target variable. 

My first idea was to convert the time of occurrence into numbers from 1 to 5 and then for example use logistic regression. 

Do You know any other practices? 
Any whitepapers and ideas will be helpful.
If the order in which the events appears matters, consider using a recurrent neural network. The setup that you propose is invariant to event ordering, whereas in a RNN the events are fed in in sequential order.