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This project forked from sharanyaa/nlp_naivebayes_textclassifier

Language: Python Created a naive Bayes text classifier (nblearn.py, nbclassify.py) and compared accuracy with two popular machine learning toolkits. Worked with two datasets (emails and IMDB reviews) and performed binary classification: SPAM or HAM (not spam), and POSITIVE or NEGATIVE (sentiment analysis). Compared three machine learning techniques for making these classifications: naive Bayes classification, maximum entropy modeling, and support vector machines (MegaM and SVM-Light). report.txt - contains detailed instructions about the sequence of scripts to run and what cmd arguments to pass each python script.