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This study analyzes advanced machine learning techniques for detecting fake news, highlighting the effectiveness of various algorithms including Random Forest, SVM, Neural Networks, Logistic Regression, and Naïve Bayes. The Random Forest Classifier achieved the highest accuracy of 99.95%, demonstrating its robustness in distinguishing between real and fake news. The research emphasizes the importance of sophisticated preprocessing and feature engineering in developing scalable and effective fake news detect

Author

reyiy24403

Language

EN