GitHub / rishabh-karmakar / Detection-of-Real-or-Fake-News
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.
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PURL: pkg:github/rishabh-karmakar/Detection-of-Real-or-Fake-News
Stars: 2
Forks: 0
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 11.7 MB
Dependencies parsed at: Pending
Created at: over 5 years ago
Updated at: about 5 years ago
Pushed at: over 5 years ago
Last synced at: 6 months ago
Topics: news, nlp, passive-aggressive, passive-aggressive-classifier, real-fake-news, sklearn, sklearn-vectorizer, text, text-classification, tfidf, tfidf-text-analysis, tfidf-vectorizer