A Conceptual Introduction to Classification and Forecasting

Abstract

Because the criminal justice outcomes to be forecast are usually categorical (e.g., fail or not), this chapter considers crime forecasting as a classification problem. The goal is to assign classes to cases. There may be two classes or more than two. Machine learning is broadly considered before turning to random forests as the preferred forecasting tool. The approach is conceptual rather than formal. Some readers may find the material challenging, but the stage is being set for demanding material in chapters to come.