Crime Analysis Through Machine Learning

This paper investigates machine-learning-based crime prediction. In this work, Vancouver crime data for the last 15 years is analyzed using two different data-processing approaches. Machine-Learning predictive models, K-nearest-neighbour and boosted decision tree, are implemented and a crime prediction accuracy between 39% to 44% is obtained when predicting crime in Vancouver.