Prediction of crime location in a brazilian city using regression techniques
Andrio Rodrigo Corrêa da Silva, Ialis Cavalcante de Paula, Ticiana L. Coelho da Silva, José Antônio Fernandes de Macêdo, Wellington Clay Porcino Silva · 2020
There are relevant rates of violence in Brazil that have increased in recent years. Intelligence and efficiency are required to combat this issue, in order to reduce public money spending and time from public officials. Consequently, this operation may improve the safety of the population. There are several solutions that use intelligent systems to predict where and when a crime will occur, which allows police routes to be sent to areas with a higher risk of danger. In this paper, four machine learning methods are used to predict the location of where a crime will occur in a city of Fortaleza, Brazil. The final result shows that simple algorithms can be efficient in the task of crime prediction. In this paper, the Decision Tree and Bagging Regressor methods obtained the best predictions results.