research-article

Comparison on Feature Selection Methods for Text Classification

Authors:

Ming HongAuthors Info & Claims

ICMSS 2020: Proceedings of the 2020 4th International Conference on Management Engineering, Software Engineering and Service Sciences

Pages 82 - 86

https://doi.org/10.1145/3380625.3380677

Published: 19 May 2020 Publication History

Abstract

The high-dimensional text data always contains a large quantity of noisy terms which bring negative effects on the performance of text classification. Feature selection is the common solution for dimension reduction in text classification. The choices of feature selection methods for text classification have significant impacts on classification accuracy. According to our literature review, few recent studies of feature selection focus on performance comparisons on feature selection methods. To fill this gap, this paper conducts discussions to compare performances of typical feature selection methods which are commonly involved in previous studies for text classification. Firstly, we introduce and discuss a series of typical feature selection methods in previous studies for text classification in details. Secondly, we conduct comparison experiments on four benchmark datasets to compare the effectiveness of twenty typical feature selection methods in text classification. Finally, we give conclusions on performance of the typical feature selection methods. The result of this paper gives a guideline for selecting appropriate feature selection methods for text classification academic analysis or real-world text classification applications.

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Cited By

Reusens MStevens ATonglet JDe Smedt JVerbeke Wvanden Broucke SBaesens B(2024)Evaluating text classification: A benchmark studyExpert Systems with Applications10.1016/j.eswa.2024.124302254(124302)Online publication date: Nov-2024
https://doi.org/10.1016/j.eswa.2024.124302
Teng TVarathan KCrestani F(2024)A comprehensive review of cyberbullying-related content classification in online social mediaExpert Systems with Applications10.1016/j.eswa.2023.122644244(122644)Online publication date: Jun-2024
https://doi.org/10.1016/j.eswa.2023.122644
Cao PHe GYang T(2023)TF-Predictor: Transformer-Based Prerouting Path Delay Prediction FrameworkIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.321675242:7(2227-2237)Online publication date: Jul-2023
https://doi.org/10.1109/TCAD.2022.3216752
Show More Cited By

Index Terms

Comparison on Feature Selection Methods for Text Classification
1. Computing methodologies
  1. Machine learning
    1. Machine learning algorithms
      1. Feature selection

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ICMSS 2020: Proceedings of the 2020 4th International Conference on Management Engineering, Software Engineering and Service Sciences

January 2020

301 pages

ISBN:9781450376419

DOI:10.1145/3380625

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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China University of Geosciences

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Publication History

Published: 19 May 2020

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ICMSS 2020: 2020 4th International Conference on Management Engineering, Software Engineering and Service Sciences

January 17 - 19, 2020

Wuhan, China

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Cited By

Reusens MStevens ATonglet JDe Smedt JVerbeke Wvanden Broucke SBaesens B(2024)Evaluating text classification: A benchmark studyExpert Systems with Applications10.1016/j.eswa.2024.124302254(124302)Online publication date: Nov-2024
https://doi.org/10.1016/j.eswa.2024.124302
Teng TVarathan KCrestani F(2024)A comprehensive review of cyberbullying-related content classification in online social mediaExpert Systems with Applications10.1016/j.eswa.2023.122644244(122644)Online publication date: Jun-2024
https://doi.org/10.1016/j.eswa.2023.122644
Cao PHe GYang T(2023)TF-Predictor: Transformer-Based Prerouting Path Delay Prediction FrameworkIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.321675242:7(2227-2237)Online publication date: Jul-2023
https://doi.org/10.1109/TCAD.2022.3216752
Markkandeyan SSelvam LTamizharasu KAandi S(2023)Experimental Analysis of the Machine Learning Algorithms for Crime Web Page ClassificationIETE Journal of Research10.1080/03772063.2023.222251370:5(4890-4902)Online publication date: 13-Jun-2023
https://doi.org/10.1080/03772063.2023.2222513
Abiodun EAlabdulatif AAbiodun OAlawida MAlabdulatif AAlkhawaldeh R(2021)A systematic review of emerging feature selection optimization methods for optimal text classification: the present state and prospective opportunitiesNeural Computing and Applications10.1007/s00521-021-06406-833:22(15091-15118)Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.1007/s00521-021-06406-8

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