A Comparative Study Between Naive Bayes and Neural Network (MLP) Classifier for Spam Email Detection

The continue demands of internet and email communication has creating spam emails also known unsolicited bulk mails. These emails enter bypass in our mail box and affect our system. Different filtering techniques are using to detect these emails such as Random Forest, Naive Bayesian, SVM and Neural Network. In this paper, we compare the different performance matrices using Bayesian Classification and Neural Network approaches of data mining that are completely based on content of emails. Proposed method are based on data mining approach, that provides an anti spam filtering technique that segregate spam and ham emails from large dataset. Methodologies that are used for the filtering methods are machine learning techniques using ANN and Bayesian Network based solutions. This approach practically applied on Trec07 dataset.