Electronic Mail Classification System Based on Machine Learning approach

In current times, users depend comprehensively on electronic communication ways such as electronic mails as it is considered a foremost source of communication. A vast amount of time is invested in electronic mail for communication in the information technology field, due to which electronic mail management has become a prominent feature among the mailing applications. Electronic mail classification comes under this type of management which helps the expert to eliminate the time invested during un-necessary mail reading. Also, the content of electronic mail is further used in the analysis for future prediction and reading behaviors in which a good mail classification system would reduce a lot of time and resources. Conventionally many other systems or methods are present and widely popular in the market but there is no such system that achieves high accuracy. This paper proposes a novel electronic mail classification system that is based ensemble technique which combines the result of many classifiers to achieve good accuracy.