Spam Email Filtering using Machine Learning Algorithm

Email is one of the most used modes of communication by many industries and IT sectors. Even common people used to communicate through email about business related in-formation over the internet As technology grows, the threat to the individual has also been increased. In the Email system, the threat takes the form of spam email. There are several existing spam filtering methods currently in use including knowledge-based techniques, learning-based techniques, clustering methods, and so on. The proposed work provides an overview of several existing methods that use Machine learning techniques such as Naive Bayes, Support Vector Machine, Random Forest, Neural Network and formulated new model with improved accuracy. However, in this work, the discussion and consolidated analysis has been done by comparing several email spam filtering techniques.