I am trying to predict future sales from past transactional data with a neural network. My data looks something like this:
Customer, Transaction_Num, Sales, Product, Date, ... About 50 more categorical variables
I would like the network to learn from these transactional rows and predict next week's sales.
The best way I can think of to structure this data is to sum up all data for each week and put it in a column, like so:
Week t Sales, Week t-1 Sales, Week t-2 Sales, etc for all 50+ variables * # of weeks
And for a lot of the variables it wouldn't make sense to sum or average them.
Is there a better way of doing this?