Analysis and Prediction of Location based Criminal Behaviors Through Machine Learning

Criminal Behaviors may be predicted, identified, and prevented via data mining. The research of criminal activity and its features is known as criminology. To be more accurate, crime analysis entails investigating and detecting crimes and their connections to convict. Because of the vast number of criminal record and intricacy of the linkages between different types of data, criminology is an excellent place to use data mining techniques. The first stage in doing more research is to identify criminal traits. This study offered an overview of current work in the field of crime prevention or prediction using data mining and machine learning technologies. For the system to learn, a year's worth of crime data is fed into it from a reliable Indian internet source that focuses on murder, kidnapping and abduction as well as dacoits and burglars and rape. To anticipate crime rates in different states, a regression model is created using Indian statistics, which provides data on a wide range of crimes over the last few years. A variety of Machine Learning techniques, including unsupervised, semi-supervised, and supervised learning, are used to improve the accuracy of crime predictions. Local police stations will benefit from this effort with regards to crime avoidance. The results may help policymakers better understand crime prediction and prevention.