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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Toward Accurate Feature Selection Based on BSS-GRF

Author 1: S. M. Elseuofi Author 2: Samy Abd El -Hafeez Author 3: Wael Awad Author 4: R. M. El-Awady
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 5, No. 8 · Published 2014

DOI: https://doi.org/10.14569/IJACSA.2014.050808

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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.

Keywords

rough set Genetic blind source separation E-mail Filtering Machine Learning

How to Cite this Article

Elseuofi, S. M., -Hafeez, S. A. E., Awad, W., & El-Awady, R. M. (2014). Toward Accurate Feature Selection Based on BSS-GRF. International Journal of Advanced Computer Science and Applications, 5(8). https://doi.org/10.14569/IJACSA.2014.050808

Elseuofi, S. M., et al.. "Toward Accurate Feature Selection Based on BSS-GRF." International Journal of Advanced Computer Science and Applications, vol. 5, no. 8, 2014, https://doi.org/10.14569/IJACSA.2014.050808.

@article{Elseuofi2014,
  title     = {Toward Accurate Feature Selection Based on BSS-GRF},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {5},
  number    = {8},
  year      = {2014},
  publisher = {The Science and Information Organization},
  author    = {S. M. Elseuofi and Samy Abd El -Hafeez and Wael Awad and R. M. El-Awady},
  doi       = {10.14569/IJACSA.2014.050808},
  url       = {https://doi.org/10.14569/IJACSA.2014.050808}
}

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