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Machine Learning for Fake News Detection by taber bin zameer is a document available to read on EtoBox.
What is Machine Learning for Fake News Detection about?
This document describes a project to develop a machine learning model to identify fake or unreliable news based on content. It tests several models including Naive Bayes, SVM, neural networks, and LSTM on a labeled news dataset. The LSTM model achieved the highest accuracy of 94.53%. Challenges included lack of clean data. Future work could include combining classifiers and checking news sources and content.
- Author
- taber bin zameer
- Language
- EN