What is it about?
This paper inspects the capability of Extreme Learning Machine for email spam filter.The ELM method is an efficient model based on single layer feedforward neural network, which can choose weights from hidden layers,randomly. Support vector machine is a strong statistical learning theory used frequently for classification. The performance of ELM has been compared with SVM. The comparative study examines accuracy, precision, recall, false positive and true positive.Moreover, a sensitivity analysis has been performed by ELM and SVM for spam email classification.
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Why is it important?
ELM is one of the hottest ML techniques designed by Huang, Guang-Bin in the year 2006.This paper projects an interesting concept of ELM application in spam emails classification. No one has reported a model for SPAM filter using ELM before.
Perspectives
Dr. Sanjiban Sekhar Roy is with School of Computer Science and Engineering(SCOPE), VIT University, Vellore, Tamilnadu, India since 2009. He holds a B.E degree in Information Technology , M.Tech & Ph.D. degree in Computer Science and Engineering. His research interests include machine learning, data mining and network security. He has to his credit various articles published in international journals and conferences. Mailing address: SJT-116-A29, SCOPE, VIT University, Vellore, Tamilnadu, India. Pin: 632014.
Dr. Sanjiban Sekhar Roy
VIT University
Read the Original
This page is a summary of: Classifying Spam Emails Using Artificial Intelligent Techniques, International Journal of Engineering Research in Africa, February 2016, Trans Tech Publications,
DOI: 10.4028/www.scientific.net/jera.22.152.
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