Comparative Study of Different Machine Learning Algorithms for Fake News Detection: A TF-IDF Approach |
Author(s): |
| Lakshya Chugh , Maharaja Agrasen Institute Of Technology; Mayank Kathuria, Maharaja Agrasen Institute Of Technology; Bhaskar Kapoor, Maharaja Agrasen Institute Of Technology |
Keywords: |
| Classification Algorithms, Fake News, Logistic Regression, Machine Learning, Random Forest, Supervised Learning, TF-IDF, Tokenizing, XGBoost |
Abstract |
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In this paper we examine the results of training models and then testing accuracy of three machine learning algorithms in the context of fake news detection applying Term Frequency Inverse Document Frequency (TF-IDF) as the underlying principle to determine which of the said algorithms would be more suited to solve the problem. |
Other Details |
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Paper ID: IJSRDV6I20394 Published in: Volume : 6, Issue : 2 Publication Date: 01/05/2018 Page(s): 388-392 |
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