Ensemble classification approach for email spam filtering

E-mail has become a significant mean of message sharing. A perfect way is obtained through email for sending this enormous volume of ads without any expenditure for the forwarder and bitter reality is a number of organizations make the utilization of this in these days. The email spam detection has various phases which include pre-processing, feature extraction and classification. In this voting classification is proposed which is the combination of random forest, naive bayes and SVM. The proposed method is implemented in python and results are analyzed in terms of accuracy, precision and recall.