Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Comparison of different optimization algorithms. by Hang Zhao (143592)

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Ranking of ML algorithms. by Yasemin Ayaz Atalan (21989402)

“…The RF algorithm performed best with the lowest mean absolute percentage error (MAPE, 0.084%), mean absolute error (MAE, 0.035), root mean square error (RMSE, 0.063), and mean squared error (MSE, 0.004) values in the test dataset. …”

Performance of models by different algorithms. by Yong Zhang (5893)

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The overview of the ML algorithms’ flowchart. by Yasemin Ayaz Atalan (21989402)

“…The RF algorithm performed best with the lowest mean absolute percentage error (MAPE, 0.084%), mean absolute error (MAE, 0.035), root mean square error (RMSE, 0.063), and mean squared error (MSE, 0.004) values in the test dataset. …”

RFEcv algorithm flowchart. by Xinrui Wang (488330)

Variables tested in the ML algorithms. by Gilson Yuuji Shimizu (19837946)

“…Shapley values for local interpretability were more informative than LIME ones, which is in line with our exploratory analysis and global interpretation of the final model. Machine learning algorithms with good generalization and accompanied by interpretability analyses are recommended for assessments of individual risks of cardiovascular diseases and development of personalized preventive actions.…”

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Flowchart of the artificial bee colony algorithm. by Wei Su (89824)

“…This study proposes a hybrid model (MABC-LSSVM) that combines a modified artificial bee colony (MABC) optimization algorithm with a least squares support vector machine (LSSVM) model. …”

Development of the CO₂ Adsorption Model on Porous Adsorbent Materials Using Machine Learning Algorithms by Hossein Mashhadimoslem (11456548)

S1 Syntax - Application of machine learning algorithms to predict early childhood development in children aged 24–59 months across three East African countries by Tsion Mulat Tebeje (13955254)

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Performance evaluation of the machine learning models to predict early childhood development in East Africa. by Tsion Mulat Tebeje (13955254)

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Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Comparison of information on predicting survival outcomes or metastasis of cancer patients using machine learning algorithms in the past. by Jingru Dong (14076094)

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Schematic diagram of the experimental algorithm. by Ronghua Meng (20978441)

“…On the basis of stable egg carrying, a carrying motion mathematical model is established, and the genetic algorithm (GA) is chosen to optimize the structural parameters. …”

AUROC scores with 95% CI from Day 1 to Day 4 for different algorithms. by Armin Abdollahi (21440129)

Learning curves under various machine algorithms. by Jinlin Teng (17972595)

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ROC curves under various machine algorithms. by Jinlin Teng (17972595)

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