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What is Email Classification with Naive Bayes about?

The document describes an email classification system that uses a Naive Bayes classifier. It analyzes a dataset of 5,500 emails labeled as either important or spam. The system pre-processes the emails by stripping HTML, removing stopwords, and applying techniques like stemming. It then trains a Naive Bayes classifier on this dataset, using the words in each email as features. The trained classifier can classify new emails as important or spam based on the presence of words. The Naive Bayes approach is advan

Author

FHIT Chikkabanavara

Language

EN