- Achieved naive Bayes classifier implementation with Count based and TF-IDF based vectors.
- The accuracy is the same with the NB in sklearn
- 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,)