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It classifies news articles as **Real** or **Fake** based on their textual content.\n\nThe system uses:\n- Text preprocessing and TF-IDF vectorization\n- Two classification models:  \n  - **Multinomial Naive Bayes** (for probability predictions)  \n  - **Passive Aggressive Classifier** (for high accuracy)\n\n## Features\n- Clean and preprocess news text for NLP modeling\n- Convert text to TF-IDF feature vectors\n- Train and compare two models:\n  - Multinomial Naive Bayes\n  - Passive Aggressive Classifier\n- Save and load trained models for offline use\n- Predict batch news articles\n- Output prediction probabilities with Passive Aggressive Classifier model\n- Easy-to-use prediction function for real-time testing\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsabin74%2Ffake_news_detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsabin74%2Ffake_news_detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsabin74%2Ffake_news_detection/lists"}