Disciplines
Artificial Intelligence and Robotics
Abstract (300 words maximum)
Classification is an important technique to deal with cybersecurity threats. In this paper, we detect spam emails from publicly available dataset using Naive Bayes and Neural Network (NN). The results from experiments show that for data sets with more balanced for classification, the accuracy of Naive Bayes is better than NN
Academic department under which the project should be listed
CCSE - Computer Science
Primary Investigator (PI) Name
Hossain Shahriar
Included in
Spam Email Detection: Comparison Between Naïve Bayes and Neural Network
Classification is an important technique to deal with cybersecurity threats. In this paper, we detect spam emails from publicly available dataset using Naive Bayes and Neural Network (NN). The results from experiments show that for data sets with more balanced for classification, the accuracy of Naive Bayes is better than NN