Criminal Conviction Classification Based on Multiple Learning Methods

Abstract

The application of artificial intelligence in the legal field can save a lot of the time for legal professionals. In particular, in this paper we propose a method for predicting what kind of conviction a suspect has according to the facts of the crime of the suspect. Specifically, we first pre-process the data and then use multiple classification methods to classify the crime facts, and finally combine the results of each model to gain a more accurate of conviction classification.