A Comparative Study on Crime Analysis Techniques

Crime analysis and prevention is a systematic approach for identifying and analyzing patterns and trends in crime. Crime analytics and prediction have long been studied among research communities. In the daily life, crime keeps increasing and threatens the lives of the people in public. In this paper, various existing techniques like k-means algorithm, k-nearest neighbor algorithm, Naïve Bayes’ theorem, decision trees, random forest, Apriori algorithm, logistic regression, linear regression, SVM and neural networks are summarized.