Crime data has two specific dimensions — geographic and temporal (crimes happen in different places at different times). Additional data sets provide other information on the weather, neighborhood, and public transportation that can impact the final model. Not every point in time and space is equally likely to host a crime, but machine learning can leverage this data to help understand the factors that contribute to historical crime and even predict future crimes.