Using Machine Learning Techniques for Predicting Email Spam

The email has become one of the most efficient and cost-effective methods communication in recent years. However, as number users grows, so does spam emails. Email management a big rising concern for both people companies consequence its sensitivity to abuse. Spam, or unsolicited sending unwanted messages, is example misuse. Spam defined bulk email, sent large without their consent. Half receive 10 more emails each day, while some hundreds per day. Online spiders are used by many spammers discover addresses on web pages. Because can fill up storage space file server quickly, they could cause very severe problem websites with thousands this study; we present method filtering using machine learning techniques predict whether an no.