Predictive Analytics of Crime Data using Supervised and Ensemble Learning Methods

Predictive analytics involves using data and machine learning techniques to determine the probability of future outcomes based on large amounts of data. Criminal acts are a part of society in every way, whether as an offender or a victim, it is inevitable that every individual has seen a criminal act. The predictive analytics approach has been used to analyze the crime data. It is achieved using a data set containing crime records. Many events of crimes are present in the crime data set. Based on the location of the crimes,the trends of crime have been analysed, based on where it happened the most, and time(week)over the years.The prediction of crimes based on time, location, and other parameters has been performed using supervised machine earning techniques including K-Nearest Neighbour, Random forest and ensemble methods.