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NBClassifier

This project is about creating a supervised NB classifier. This is a 2 step process:

  1. It creates a NB model from already tagged data.
  2. Use this model to tag unseen data.

In this project we are revieweing the reviews of hotels and classifying into 4 tags :

  1. Positive
  2. Negative
  3. Truthful
  4. Deceptive

We use Naive Bayes theorem to construct a NB Model. we build the model using a corpus which is already tagged by a human. From the tagged sentenses, we build the NB Classifier. For handling unseen words, we perform Laplace Smoothing by performing add 1 smoothing. The accuracy of this model is 0.90

This is written in Python

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Naive Bayes Classifier

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