Mining Criminal Dataset Using Gradient Boosting Algorithm

Abstract

Data mining is a process for evaluating & testing huge remaining databases towards produce novel data that can be necessary for association. Using existing datasets is predicted to remove new information. There have been many approaches to data mining analysis and prediction. But there have been only several attempts in the field of crime science. Very few people have tried to compare all of these approaches which are with the information produced by them. Police stations & further related criminal justice agencies maintain big databases of data that may expect or examine criminal activity & criminal activity into community. We may too predict criminals built proceeding crime statistics. On basis of these subjects, we have used the concept of data mining to predict the criminology and the reasons behind the occurrences of the crime. The proposed algorithm is able to predict more significant features with higher accuracy and efficiency.