Improving E-Mail Spam Classification using Ant Colony Optimization Algorithm

D. Karthika Renuka, P. Visalakshi, T. Jai Sankar · 2015

In recent days, Electronic mail system is a store and forward mechanism used for the purpose of exchanging documents across computer network through Internet. Spam is an unwanted mail which contains unsolicited and harmful data that are irrelevant to the specified users. In the proposed system, the spam classification is implemented using Naive Bayes classifier, which is a probabilistic classifier based on conditional probability applicable for more complex classification problems. Implementation of feature selection using hybrid Ant Colony Optimization serves to be more efficient which gives good results for the above system that has been proposed in this paper.

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