Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data

Oluwabukunmi Oyegbile; Faisal Saeed; Samer Bamansoor

doi:10.1007/978-3-031-59707-7_26

Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data

Oluwabukunmi Oyegbile^*, Faisal Saeed, Samer Bamansoor

^*Corresponding author for this work

Birmingham City University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Original language	English
Title of host publication	Lecture Notes on Data Engineering and Communications Technologies
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	293-305
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-031-59707-7_26
Publication status	Published (VoR) - 2024

Publication series

Name	Lecture Notes on Data Engineering and Communications Technologies
Volume	211
ISSN (Print)	2367-4512
ISSN (Electronic)	2367-4520

Keywords

cancer classification
genetic algorithm
hybrid Feature Selection
microarray dataset

Access to Document

10.1007/978-3-031-59707-7_26

Cite this

Oyegbile, O., Saeed, F., & Bamansoor, S. (2024). Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data. In Lecture Notes on Data Engineering and Communications Technologies (pp. 293-305). (Lecture Notes on Data Engineering and Communications Technologies; Vol. 211). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-59707-7_26

Oyegbile, Oluwabukunmi ; Saeed, Faisal ; Bamansoor, Samer. / Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data. Lecture Notes on Data Engineering and Communications Technologies. Springer Science and Business Media Deutschland GmbH, 2024. pp. 293-305 (Lecture Notes on Data Engineering and Communications Technologies).

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author = "Oluwabukunmi Oyegbile and Faisal Saeed and Samer Bamansoor",

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Oyegbile, O, Saeed, F & Bamansoor, S 2024, Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data. in Lecture Notes on Data Engineering and Communications Technologies. Lecture Notes on Data Engineering and Communications Technologies, vol. 211, Springer Science and Business Media Deutschland GmbH, pp. 293-305. https://doi.org/10.1007/978-3-031-59707-7_26

Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data. / Oyegbile, Oluwabukunmi; Saeed, Faisal; Bamansoor, Samer.
Lecture Notes on Data Engineering and Communications Technologies. Springer Science and Business Media Deutschland GmbH, 2024. p. 293-305 (Lecture Notes on Data Engineering and Communications Technologies; Vol. 211).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Oyegbile, Oluwabukunmi

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Oyegbile O, Saeed F, Bamansoor S. Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data. In Lecture Notes on Data Engineering and Communications Technologies. Springer Science and Business Media Deutschland GmbH. 2024. p. 293-305. (Lecture Notes on Data Engineering and Communications Technologies). doi: 10.1007/978-3-031-59707-7_26

Hybrid Filter Feature Selection for Improving Cancer Classification in High-Dimensional Microarray Data

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