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- W4285183268 abstract "During the covid 19 outbreak, fake news has grown highly, affecting people’s mental and physical health. There is a wide range of solutions for fake news classification which are machine learning-based proposed models. Research shows that the existing proposed models have less accuracy, and they are only text-based models. In our research paper, we are focused on different algorithms, and we are comparing these algorithms in our proposed model in this research paper. We are considering the title author and text in the proposed model. Based on our experiments, Logistic Regression has high accuracy, recall, and precision score values. This research paper suggests using a logistic regression model to classify fake news." @default.
- W4285183268 created "2022-07-14" @default.
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- W4285183268 date "2022-01-01" @default.
- W4285183268 modified "2023-09-27" @default.
- W4285183268 title "Ensemble approach for fake news classification using machine learning" @default.
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- W4285183268 doi "https://doi.org/10.1051/itmconf/20224403017" @default.
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