Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2014.050808
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 8, 2014.
Abstract: As of late, Feature extraction in email classification assumes a vital part. Many Feature extraction algorithms need more effort in term of accuracy. In order to improve the classifier accuracy and for faster classification, the hybrid algorithm is proposed. This hybrid algorithm combines the Genetics Rough set with blind source separation approach (BSS-GRF). The main aim of proposing this hybrid algorithm is to improve the classifier accuracy for classifying incoming e-mails.
S. M. Elseuofi, Samy Abd El -Hafeez, Wael Awad and R. M. El-Awady, “Toward Accurate Feature Selection Based on BSS-GRF” International Journal of Advanced Computer Science and Applications(IJACSA), 5(8), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050808