Open AccessSuspect Prediction Based on Naive Bayesian Method
Author(s) -
Zixuan Hu
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/631/3/032054
Subject(s) - suspect , terrorism , bayesian probability , naive bayes classifier , python (programming language) , computer science , machine learning , bayesian inference , artificial intelligence , computer security , psychology , data mining , criminology , political science , support vector machine , law , programming language
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.