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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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

Feature selection process. by Balraj Preet Kaur (20370832)

The performance of classifiers based on 60 selected mRNAs. by Seyed Mahdi Hosseiniyan Khatibi (16791475)

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Study selection. by Sebastião Rogério da Silva Neto (11944944)

List of selected mRNAs in the feature selection step. by Seyed Mahdi Hosseiniyan Khatibi (16791475)

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Selected mRNAs based on association rule mining analysis, for early and late stages of PTC. by Seyed Mahdi Hosseiniyan Khatibi (16791475)

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The maximum accuracy (lowest error rate) with the least number of ANOVA-ranked genes achieved by different feature filtering methods and classification algorithms refined by SIRRFE... by Song Cui (553627)

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging by D. Andrew Brown (6584837)

Dataset selection process and exclusion criteria. by Seung Seog Han (4782486)

The performance of the SVM classifier based on 60 (30 plus 30-zeroed) selected mRNAs for GSE 60542 dataset. by Seyed Mahdi Hosseiniyan Khatibi (16791475)

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

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

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Top mRNAs based on repeat count in early-stage and late-stage rules. by Seyed Mahdi Hosseiniyan Khatibi (16791475)

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Twenty of the top early-stage and late-stage rules based on sorted lift value. by Seyed Mahdi Hosseiniyan Khatibi (16791475)

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Performance of the ceRNAR package using synthetic data with randomly selected correlation values from 0.8 to 0.9. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.3 to 0.9. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.5 to 0.7. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.3 to 0.4. by Yi-Wen Hsiao (13767916)

Medium-scale dataset comparative analysis using the number of features selected. by Olaide N. Oyelade (14047002)

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