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Notebook for NLP Feature Engineering

Based on Alice Zheng’s great book on feature engineering, you can find Alice’s repo here.

This is notebook used the yelp challenge dataset to illustrate feature extraction and engineering for natural language processing (NLP). A very simple logistic regression model was used to classify the categories business type, i.e., ['Nightlife', 'Restraunts']. Methods used for tokenizing text reviews are:

  • bag-of-word (word counting)
  • n-gram
  • term frequency-inverse document frequency normalization
  • L2 normalization

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