Iterative Feature Selection Using Information Gain & Naïve B…

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  • DOI 10.1109/iccitechn.2018.8631971
  • OpenAlex ID W2915012007
  • Type Conference-paper
  • Language EN
  • Published 01 Dec 2018
  • Pages 1–6
  • Countries 1
  • Institutions 2
  • Added 10 Oct 2025
  • Updated 01 Oct 2026
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Iterative Feature Selection Using Information Gain & Naïve Bayes for Document Classification

Conference-paper 2018 EN

Data Mining is the technique of analyzing large amount of data to determine the relation among large dataset. In this paper, we are discussing a new method for document classification. Usually Document classification has been done by using classifier algorithms. Naïve Bayes classifier is frequently used for classification which provides more accurate result for larger dataset. The usage of informa…

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4 authors
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1 Chowdhury Mofizur Rahman United International Universit… (BD) —
2 Lameya Afroze Military Institute of Science … (BD) —
3 Naznin Sultana Refath Military Institute of Science … (BD) —
4 Nafin Shawon Military Institute of Science … (BD) —

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