I have a data set of transactions and want to build a fraud detection model (classifier). Only 3 variables are given that could be used as input features. The number of transactions during past 3, 6 and 12 months. These three features are highly correlated. I want to use the information content in all three features as much as possible. What is the best way to handle their great amount of correlation.