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  • 标题:Toward Accurate Feature Selection Based on BSS-GRF
  • 本地全文:下载
  • 作者:S. M. Elseuofi ; Samy Abd El -Hafeez ; Wael Awad
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2014
  • 卷号:5
  • 期号:8
  • DOI:10.14569/IJACSA.2014.050808
  • 出版社:Science and Information Society (SAI)
  • 摘要: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.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; rough set; Genetic; blind source separation; E-mail Filtering; Machine Learning
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