RT Book
T1 To be or not to be? A spatial predictive crime model for Rochester
A1 Acharyya, Rupam
A2 Tanveer, Md Iftekar
A2 Shivkumar, Sabyasachi
A2 Chattoraj, Ankani
A2 Ali, Mohammad Rafayet
LA English
YR 2020
UL https://krimdok.uni-tuebingen.de/Record/186660824X
AB This project uses a spatial model (Geographically Weighted Regression) to relate various physical and social features to crime rates. Besides making interesting predictions from basic data statistics, the trained model can be used to predict on the test data. The high accuracy of this prediction on test data then allows us to make predictions of crime probabilities in different areas based on the location, the population, the property rate, the time of the day/year and so on. This then further gives us the idea that an application can be built to help people traveling around Rochester be aware when and if they enter crime prone area