朴素贝叶斯分类器
计算机科学
人工智能
分类器(UML)
贝叶斯分类器
机器学习
贝叶斯定理
软件
模式识别(心理学)
试验装置
数据挖掘
贝叶斯概率
支持向量机
程序设计语言
作者
Mykhailo Granik,Volodymyr I. Mesyura
出处
期刊:2017 IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON)
日期:2017-05-01
被引量:312
标识
DOI:10.1109/ukrcon.2017.8100379
摘要
This paper shows a simple approach for fake news detection using naive Bayes classifier. This approach was implemented as a software system and tested against a data set of Facebook news posts. We achieved classification accuracy of approximately 74% on the test set which is a decent result considering the relative simplicity of the model. This results may be improved in several ways, that are described in the article as well. Received results suggest, that fake news detection problem can be addressed with artificial intelligence methods.
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