Feature selection convergence time comparison of various binary metaheuristic algorithms. by Amal H. Alharbi (21755906)

Number of features selected for IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Sensitivity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Specificity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Fitness values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Fig 7 - by Olaide N. Oyelade (14047002)

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Classification accuracy values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

F-score values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Feature selection ratio results for tested algorithms. by Nebojsa Bacanin (13932723)

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Initial parameter settings for the optimization algorithms. by Doaa Sami Khafaga (21463870)

The result of the accuracy of tested algorithms. by Nebojsa Bacanin (13932723)

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Numerical example for determining the optimal number of clusters in Algorithm 2. by Yi Wei Tye (22208735)

Bar chart comparing the average fitness values of various feature selection algorithms. by Doaa Sami Khafaga (21463870)

Hyperparameter settings for the optimization algorithms. by Ahmed M. Elshewey (21463867)

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The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

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a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

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Best fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

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Mean fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

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Standard deviation of fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

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Box plots with swarm overlays for six feature selection algorithms, annotated with mean and standard deviation values. by Doaa Sami Khafaga (21463870)