Spam Email Classification

The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Machine learning techniques now days used to automatically filter the spam e-mail in a very successful rate. In this project we build some of the most popular machine learning methods (Multinomial Bayesian classification, K-NN and SVMs) and compare their performance with respect to each other. Tools Used: LIBSVM Languages Used: Java, C++