TfidfVectorizer & PassiveAggressiveClassifier
An NLP model to detect fake news and accurately classify a piece of news as REAL or FAKE trained on dataset provided by Kaggle.
Fake News Detection using Machine Learning is a comprehensive project that utilizes machine learning and natural language processing techniques to identify and classify fake news articles. The project includes data analysis, model training, and a real-time web application for detecting fake news.
A Django webapp that detects fake news with Machine Learning.
Fake News Detection using Machine Learning Algorithms and deploying using Flask
Detecting 'FAKE' news using machine learning.
Detect Real or Fake News. To build a model to accurately classify a piece of news as REAL or FAKE. Using sklearn, build a TfidfVectorizer on the provided dataset. Then, initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.
CheckThis is a Fake News Detection website developed by Jonathan Lee as part of the Final Year Project (FYP). The aim of this project is to create a simple web application to help ease the process of verifying the validity of a news article online
This is my Machine Learning model created with PassiveAggressiveClassifier to detect a news as Real or Fake depending on it's contents.
Fake news classifier model
Penerapan TF-IDF Vectorizer dan Passive Aggressive Classifier dalam pendeteksian berita palsu dengan Python.
A simple Python model that uses TFIDF Vectorizer and Passive Agressive Classifier to detect fake and irrelevant news
This webapp helps to find the inaccurate information around the world through news
This is a simple model which first vectorizes the training data using TF-IDF and then uses Passive Aggressive Classifier to train on the input data.
A project which examines the prevalence of fake news in light of communication breakthroughs made possible by the rise of social networking sites.
Detect FAKE news using sklearn
Fake News Detection using Scikit-learn
This advanced python project of detecting fake news deals with fake and real news. Using sklearn, we build a TfidfVectorizer on our dataset. Then, we initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.
This is a flask application that detects and identifies the fake or real news.
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