tajindes / nlp_naivebayesclassifier

Naive Bayes Classifier

Name: Tajinder Singh

Steps for Naive Bayes Classifier:

1. Use preprocessing_training.py to convert TRAINING_DATA to TRAINING_FILE (spam_training.txt)
2. Then execute Naive_Bayes_learn.py to create spam.nb (MODEL FILE)
3. Use preprocessing_test.py to convert TEST_DATA to test file format.
4. Then execute Naive_Bayes_classify.py to create spam.out using TEST_FILE and MODEL_FILE. syntax is: "python3 Naive_Bayes_classify spam.nb TESTFILE > spam.out"

Similar steps for Sentiment analysis.

Precision, Recall and F-score on the development data for Naive Bayes Classifier for each of the two datasets:

SPAM Dataset: class: SPAM precision for class SPAM is: 0.9587912087912088 recall for class SPAM is: 0.9614325068870524 F-SCORE for class SPAM is: 0.9601100412654747 class: HAM precision for class HAM is: 0.985985985985986 recall for class HAM is: 0.985 F-SCORE for class HAM is: 0.9854927463731865

SENTIMENT Dataset: class: NEG precision for class NEG is: 0.8271947527749748 recall for class NEG is: 0.8744 F-SCORE for class NEG is: 0.8501425978739953 class: POS precision for class POS is: 0.8667986425339367 recall for class POS is: 0.8173333333333334 F-SCORE for class POS is: 0.8413395553115566