DEEP LEARNING APPROACHES FOR CRIME PATTERN ANALYSIS AND FORECASTING

Abstract

Crime affects individuals and society today. A nation's population becomes unpredictable when crime rises. We must understand crime trends to assess and predict this type of crime. This project predicts criminal conduct using crime trend analysis and open-source Kaggle crime data. This inquiry seeks to identify the most common crime, where it occurs, and when. This project categorizes criminal tendencies using machine learning approaches like Naïve Bayes. It operates more precisely than prior research.