Abstract
The purpose of this study is to design a fake news detection system with these three machine learning models, namely: Decision Tree, Random Forest, and Logistic Regression. These three different models were analysed to determine the most efficient model for accurately detecting fake news. The result obtained showcased Logistic Regression with an accuracy of 98.80%, Decision Tree with an accuracy of 99.64% and Random Forest with an accuracy of 99.23%. It is evident as deduction from the comparative analysis that our best model came out to be Decision Tree with an accuracy of 99.64%.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: British Journal of Computer, Networking and Information Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
