Several loop patterns found in binary code. by Alba Pedro-Zapater (8600382)

Proposed Algorithm. by Hend Bayoumi (22693738)

“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”

Comparative analysis of model performance indicators and diagnostic visualizations for full-featured and simplified models across ten algorithms. by Aref Andishgar (18155608)

History of Process Transformation by de Wit Coetsee (21380672)

Input features. by Nicola Lazzarini (3528197)

Comparisons between ADAM and NADAM optimizers. by Hend Bayoumi (22693738)

“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”

Age feature importance. by Nicola Lazzarini (3528197)

ROC area for the ML algorithms applied on Dataset 3. by Murad Al-Rajab (10661360)

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Classification accuracy for the ML algorithms applied to Dataset 3. by Murad Al-Rajab (10661360)

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Classification accuracy for the ML algorithms applied to Dataset 2. by Murad Al-Rajab (10661360)

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ROC area for the ML algorithms applied to Dataset 1. by Murad Al-Rajab (10661360)

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ROC area for the ML algorithms applied to Dataset 2. by Murad Al-Rajab (10661360)

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Confusion matrix for the ML algorithms applied to Dataset 2. by Murad Al-Rajab (10661360)

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Classification accuracy for the ML algorithms applied to Dataset 1. by Murad Al-Rajab (10661360)

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Most important predictive features. by Nicola Lazzarini (3528197)

ML confusion matrix for the ML algorithms applied to Dataset 1. by Murad Al-Rajab (10661360)

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ML confusion matrix for the ML algorithms applied to Dataset 3. by Murad Al-Rajab (10661360)

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Summary of ROC area for the ML algorithms applied to all datasets. by Murad Al-Rajab (10661360)

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

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

History of the total number of births to U.S. residents per year and the adoption growth of the <i>2003 Revised Birth Certificate</i>. by Karl W. Schulz (14309461)