Authentic News Prediction in Machine Learning using Passive AggressiveAlgorithm

Due to increase of users in the online social media platform in the past few years, fake news has become a serious downside issue and are spreading like wildfire. By the inevitable widespread of fake news, humans are incapable of detecting whether the news is genuine or fake. In order to restrain many researches have been done for automatic detection of counterfeit news in Machine Learning to help people identify and avoid fake news. The proposed techniques are implemented using Natural Language Processing (NLP) Algorithm with classifier namely Passive-Aggressive with Sci-kit Python Library packages. The outcome is text-based. Here the use of Machine learning algorithm technique is put forward in classifying the news articles. A Machine Learning Algorithm Namely Passive - Aggressive Classifier (PAC) is trained. Framework like Flask is used for web development. Python packages like NumPy, Pandas, Sci-kit, NLTK, are used to train the machine. The outcome is based on URL-Search. After training and testing its implementation, a meaningful accuracy in detection has been achieved.