[20161002]Weekly Report

  1. Achieved naive Bayes classifier implementation with Count based and TF-IDF based vectors.
  2. The accuracy is the same with the NB in sklearn
  3. The speed is far slower than NB in sklearn

categories: [‘alt.atheism’, ‘talk.religion.misc’, ‘comp.graphics’, ‘sci.space’]

training set: (2034,), testing set: (1353,)

Customized:

Count: screenshot.png

TF-IDF: screenshot.png

Original:

count:screenshot.png

TF-IDF:screenshot.png

 

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