Research Article

Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data

Volume: IDAP-2023 : International Artificial Intelligence and Data Processing Symposium Number: IDAP-2023 October 18, 2023
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Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data

Abstract

In knowledge discovery, the processes of applying data cleaning, data integration, data selection-transformation, and data mining methods and obtaining meaningful information from the obtained patterns are performed, respectively. In recent years, it has become quite common to use metaheuristic optimization methods in the data selection phase. In this study, the nearest neighbor algorithm, support vector machine, and decision tree algorithms from machine learning algorithms were used on health data obtained from the University of California, Irvine. The whale optimization algorithm, salp swarm optimization, slime mould optimization, particle swarm optimization, and Harris Hawks optimization methods were used for feature selection. The obtained results were compared in detail.

Keywords

References

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Details

Primary Language

English

Subjects

Data Mining and Knowledge Discovery

Journal Section

Research Article

Publication Date

October 18, 2023

Submission Date

August 29, 2023

Acceptance Date

October 16, 2023

Published in Issue

Year 2023 Volume: IDAP-2023 : International Artificial Intelligence and Data Processing Symposium Number: IDAP-2023

APA
Gündoğdu, H., & Altay, O. (2023). Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data. Computer Science, IDAP-2023 : International Artificial Intelligence and Data Processing Symposium(IDAP-2023), 58-66. https://doi.org/10.53070/bbd.1351629
AMA
1.Gündoğdu H, Altay O. Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data. JCS. 2023;IDAP-2023 : International Artificial Intelligence and Data Processing Symposium(IDAP-2023):58-66. doi:10.53070/bbd.1351629
Chicago
Gündoğdu, Hüseyin, and Osman Altay. 2023. “Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data”. Computer Science IDAP-2023 : International Artificial Intelligence and Data Processing Symposium (IDAP-2023): 58-66. https://doi.org/10.53070/bbd.1351629.
EndNote
Gündoğdu H, Altay O (October 1, 2023) Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data. Computer Science IDAP-2023 : International Artificial Intelligence and Data Processing Symposium IDAP-2023 58–66.
IEEE
[1]H. Gündoğdu and O. Altay, “Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data”, JCS, vol. IDAP-2023 : International Artificial Intelligence and Data Processing Symposium, no. IDAP-2023, pp. 58–66, Oct. 2023, doi: 10.53070/bbd.1351629.
ISNAD
Gündoğdu, Hüseyin - Altay, Osman. “Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data”. Computer Science IDAP-2023 : INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM/IDAP-2023 (October 1, 2023): 58-66. https://doi.org/10.53070/bbd.1351629.
JAMA
1.Gündoğdu H, Altay O. Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data. JCS. 2023;IDAP-2023 : International Artificial Intelligence and Data Processing Symposium:58–66.
MLA
Gündoğdu, Hüseyin, and Osman Altay. “Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data”. Computer Science, vol. IDAP-2023 : International Artificial Intelligence and Data Processing Symposium, no. IDAP-2023, Oct. 2023, pp. 58-66, doi:10.53070/bbd.1351629.
Vancouver
1.Hüseyin Gündoğdu, Osman Altay. Evaluation of Performance of Feature Selection of Meta-Heuristic Optimization Methods in Medical Data. JCS. 2023 Oct. 1;IDAP-2023 : International Artificial Intelligence and Data Processing Symposium(IDAP-2023):58-66. doi:10.53070/bbd.1351629

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