An Adaptive Technique for Crime Rate Prediction using Machine Learning Algorithms

Abstract

Any country must give the investigation and preventive of crime top priority. There are a rising amount of cases that are still pending due to the rapid increase in criminal cases in India and elsewhere. It is proving difficult to classify and address the rising number of criminal cases. Understanding a place's trends in criminal activity is essential to preventing it from occurring. Crime-solving organisations will be more effective if they have a clear awareness of the patterns of criminal behavior that are present in a particular area. Women's safety and protection are of highest importance despite the serious and persistent problem of crime against them. This study offers predictions about the kinds of crimes that might occur in a particular location using ensemble methods. This facilitates the categorization of criminal proceedings and subsequent action in a timely manner. We are applying machine learning methods like KNN, Linear regression, SVM, Lasso, Decision tree and Random forest in order to assess the highest accuracy.