International Journal of Computer Applications
A spam has diluted the message pool, causing frustration so require an automatic processing of emails. This paper is to construct a spam model using classification technique in data mining. To accomplish this, experiments were conducted on spam dataset downloaded from the UCI machine learning repository which was classified using a popular data mining tool called WEKA. The final classification result should be '1' if it is finally spam, otherwise, it should be '0'. Email is popular mode of communication and its users are growing day-by-day.