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Feature Selection for Text Classification Using Genetic Algorithm

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Advances in Machine Intelligence and Computer Science Applications (ICMICSA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 656))

Abstract

Today’s large amount of text data makes feature classification a difficult text processing challenge. High dimensionality is the primary challenge in text processing, and feature selection is a common method for reducing dimensions. The most crucial factors in text classification are a strong text representation and a very accurate classifier. As a result, choosing the right features is essential for using machine learning algorithms effectively. Different optimization techniques, including the Genetic Algorithm (GA), have been effectively used for dimensionality reduction in the field of text classification. To evaluate the performance of GA for Feature Selection (FS), we compared the GA for FS with other filtering methods to prove the efficiency of the GA for FS, for that, we used the NB classifier and three benchmark document collections: SMS, BBC, and 20Newsgroups.

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Author information

Authors and Affiliations

  1. Laboratory of Process Engineering, Computer Science, and Mathematics at the National School of Applied Sciences, Sultan Moulay Slimane University, Khouribga, Morocco

    Salma Belkarkor & Imad Hafidi

  2. Laboratory of Mathematics and Applications, Team of Mathematics and Interactions, at the Faculty of Science and Technology, Sultan Moulay Slimane University, Beni-Mellal, Morocco

    Mourad Nachaoui

Authors
  1. Salma Belkarkor
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  2. Imad Hafidi
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  3. Mourad Nachaoui
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Corresponding author

Correspondence to Salma Belkarkor .

Editor information

Editors and Affiliations

  1. National School of Applied Sciences of Khouribga, Sultan Moulay Slimane University, Khouribga, Morocco

    Noureddine Aboutabit

  2. ENSIAS, Mohammed V University, Rabat, Morocco

    Mohamed Lazaar

  3. National School of Applied Sciences of Khouribga, Sultan Moulay Slimane University, Khouribga, Morocco

    Imad Hafidi

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Belkarkor, S., Hafidi, I., Nachaoui, M. (2023). Feature Selection for Text Classification Using Genetic Algorithm. In: Aboutabit, N., Lazaar, M., Hafidi, I. (eds) Advances in Machine Intelligence and Computer Science Applications. ICMICSA 2022. Lecture Notes in Networks and Systems, vol 656. Springer, Cham. https://doi.org/10.1007/978-3-031-29313-9_7

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