Abstract
The art of tampering with original facts has been going on since edges. The recent act of 2016 Presidential elections proceeded by Facebook and recently COVID19 brought up the term fake news detection. In this paper, we propose to use machine learning ensemble approach for automated classification of news articles. This paper revolves around to use the different classifiers of machine learning (ML) to predict if the news is literal or hoax and evaluate their performance on 5 real world datasets. Then ruling of a classifier is done based on Model Evaluation techniques and the results are tabulated and visual- ized. Experimental evaluation confirms the superior performance of our proposed ensemble learner approach in comparison to individual learners.
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