Neural Market Trends

Machine Learning Finds “Fake News” with 88% Accuracy

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My Notes:

  • Finding Fake News is a great task for machine learning
  • Editor: See the Viral Bot post here
  • Used Kaggle’s Fake News data set (13,000 articles)
  • Finalized data set = 10,558 articles
  • Plan was to go the routine spam detection route
  • Used word freq and TFIDF
  • Word freq and TFIDF can only get you so far
  • Extracted document titles and full text
  • Used a Naive Bayes Classifier
  • Used Scikit-Learn to tune parameter
  • Cross Validated accuracy = 91.7%
  • Testing on remaining 5,234 articles (out of sample data), 88.2% accuracy in identifying Fake News

Read the entire source article here.

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