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News Classifier using KNN and Naive Baye's Classifier

This is a set of simple machine learning algorithm which scrapes news websites and classifies them. Algorithms used are:

  1. KNN
  2. Naive Baye's
  3. K-Means

Brief Descriptions of the algorithms

  • KNN / Naive Baye's: For this, first we train the algorithm with a predefined set of tech articles and non-tech articles from the New York Times, and the Washington Post by scraping their respective websites. After that, we can provide a test article from another blog (Doxy Donkey), and the algorithm will label it as either 'tech' or 'non-tech'.

  • K-Means: This is a clustering algorithm that is unsupervised. First, we scrape all the articles from DoxyDonkey. Then, we vectorize it using TF-IDF, and then we apply the K-Means algorithm to it, to form 5 clusters.

Special Packages used

Scikit Learn
NLTK
BeautifulSoup

License

Open Sourced under the MIT License