This project provides a fake news detection module built with Python using machine learning and natural language processing techniques. It involves preprocessing news text by cleaning and preparing it, extracting features with TF-IDF, and training a Logistic Regression model to classify articles as "Fake" or "Real." The project includes evaluation metrics to assess the model's accuracy and effectiveness, and a prediction function for testing new articles.
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This project uses Python to create a fake news detection system. It preprocesses news text, extracts features with TF-IDF, and trains a Logistic Regression model to classify articles as "Fake" or "Real." The system includes evaluation metrics and a prediction function for testing new articles.
RealBright09/Fake-News-Detector-Using-Python
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This project uses Python to create a fake news detection system. It preprocesses news text, extracts features with TF-IDF, and trains a Logistic Regression model to classify articles as "Fake" or "Real." The system includes evaluation metrics and a prediction function for testing new articles.
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