Suspect Prediction Based on Naive Bayesian Method

Abstract

Aiming at the terrorist attacks that have happened in 2015 and 2016, which have not been organized or claimed responsibility by individuals, the suspect prediction algorithm based on naive Bayesian method is used to solve the problem of finding the perpetrators of terrorist attacks. Firstly, we select five terrorist organizations and individuals which are more harmful to terrorist attacks. Then, we use the suspect prediction algorithm based on naive Bayesian method to select the terrorist attacks that occurred in 2015 and 2016, which have not yet been organized or claimed responsibility by individuals. Finally, we use the Sklearn machine learning library of Python to calculate and get all the suspects in each incident. The probability of a suspect is the degree of suspicion.