Classification of spam email using intelligent water drops algorithm with Naïve bayes classifier

Abstract

The paper proposes an emerging evolutionary and swarm-based intelligent water drops algorithm for email spam classification. The proposed algorithm is used along with the machine learning classification technique known as naïve Bayes classifier. The intelligent water drops algorithm is used for feature subset construction, and naïve Bayes classifier is applied over the subset to classify the email as spam or not spam. The result of the hybrid method is compared with other evolutionary algorithm used with machine learning classifiers. The proposed algorithm outperforms the other hybrid algorithms.