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Year 2023, , 1506 - 1520, 01.12.2023

Mustafa Büyükkeçeci , Mehmet Cudi Okur

https://doi.org/10.35378/gujs.993763
Cited By: 3

Abstract

References

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A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning

Year 2023, , 1506 - 1520, 01.12.2023

Mustafa Büyükkeçeci , Mehmet Cudi Okur

https://doi.org/10.35378/gujs.993763
Cited By: 3

Abstract

Feature selection is a dimension reduction technique used to select features that are relevant to machine learning tasks. Reducing the dataset size by eliminating redundant and irrelevant features plays a pivotal role in increasing the performance of machine learning algorithms, speeding up the learning process, and building simple models. The apparent need for feature selection has aroused considerable interest amongst researchers and has caused feature selection to find a wide range of application domains including text mining, pattern recognition, cybersecurity, bioinformatics, and big data. As a result, over the years, a substantial amount of literature has been published on feature selection and a wide variety of feature selection methods have been proposed. The quality of feature selection algorithms is measured not only by evaluating the quality of the models built using the features they select, or by the clustering tendencies of the features they select, but also by their stability. Therefore, this study focused on feature selection and feature selection stability. In the pages that follow, general concepts and methods of feature selection, feature selection stability, stability measures, and reasons and solutions for instability are discussed.

Keywords

Feature selection Dimensionality reduction Types of feature selection Feature selection stability Stability measures

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There are 152 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Computer Engineering
Authors

Mustafa Büyükkeçeci 0000-0002-1970-8952

Mehmet Cudi Okur This is me 0000-0002-0096-9087

Publication Date December 1, 2023
Published in Issue Year 2023

Cite

APA Büyükkeçeci, M., & Okur, M. C. (2023). A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning. Gazi University Journal of Science, 36(4), 1506-1520. https://doi.org/10.35378/gujs.993763
AMA Büyükkeçeci M, Okur MC. A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning. Gazi University Journal of Science. December 2023;36(4):1506-1520. doi:10.35378/gujs.993763
Chicago Büyükkeçeci, Mustafa, and Mehmet Cudi Okur. “A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning”. Gazi University Journal of Science 36, no. 4 (December 2023): 1506-20. https://doi.org/10.35378/gujs.993763.
EndNote Büyükkeçeci M, Okur MC (December 1, 2023) A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning. Gazi University Journal of Science 36 4 1506–1520.
IEEE M. Büyükkeçeci and M. C. Okur, “A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning”, Gazi University Journal of Science, vol. 36, no. 4, pp. 1506–1520, 2023, doi: 10.35378/gujs.993763.
ISNAD Büyükkeçeci, Mustafa - Okur, Mehmet Cudi. “A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning”. Gazi University Journal of Science 36/4 (December 2023), 1506-1520. https://doi.org/10.35378/gujs.993763.
JAMA Büyükkeçeci M, Okur MC. A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning. Gazi University Journal of Science. 2023;36:1506–1520.
MLA Büyükkeçeci, Mustafa and Mehmet Cudi Okur. “A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning”. Gazi University Journal of Science, vol. 36, no. 4, 2023, pp. 1506-20, doi:10.35378/gujs.993763.
Vancouver Büyükkeçeci M, Okur MC. A Comprehensive Review of Feature Selection and Feature Selection Stability in Machine Learning. Gazi University Journal of Science. 2023;36(4):1506-20.

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