A SURVEY ON MACHINE LEARNING TECHNIQUES FOR TEXT CLASSIFICATION

This research focuses on Text Classification. Text classification is the task of automatically sorting a set of documents into categories from a predefined set. The domain of this research is the combination of information retrieval (IR) technology, Data mining and machine learning (ML) technology. This research will outline the fundam ental traits of the technologies involved. This research uses three text classification algorithms (Naive Bayes, VSM for text classification and the new technique - Use of Stanford Tagger for text classification) to classify documents into different categor ies, which is trained on two different datasets (20 Newsgroups and New news dataset for five categories).In regards to the above classification strategies, Naïve Bayes is potentially good at serving as a text classification model due to its simplicity.