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)

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

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)

Results of Holm’s step-down procedure. by Nebojsa Bacanin (13932723)

One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Top-performing model configuration and performance by algorithm type. by Uğur Ejder (22683228)

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The flowchart of the proposed algorithm. by Muhammad Ayyaz Sheikh (18610943)

“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”

IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

The statistical description of the original data set of the patients (<i>n</i> = 162). by Uğur Ejder (22683228)

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The list of parameters of the modified data set for machine learning (<i>n</i> = 162). by Uğur Ejder (22683228)

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<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

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The accuracy score change matrix following model development. by Uğur Ejder (22683228)

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The comparison of the accuracy score of the benchmark and the proposed models. by Uğur Ejder (22683228)

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