Performance comparison results of each algorithm model. by Shiya Gao (12693389)

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Evaluation metrics of the models constructed by each algorithm. by Xiaoyan Yang (259084)

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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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Average computation time for each algorithm. by Jinyu Wang (381467)

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Cost and cases diagnosed for each algorithm in different modelled scenarios. by Tushar Garg (9283574)

Results of oil detection accuracy under different oil status conditions for each algorithm. by Shiya Gao (12693389)

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Federated averaging algorithm. by Yan Qin (118276)

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

Performance of machine learning algorithms. by Wenxue Liu (6877754)

A classification scheme of bipartite randomization algorithms, based on whether the matrix row and columns sums are preserved exactly (Fixed, <i>F</i>), preserved on average (Propo... by Zachary P. Neal (9946331)

Data Sheet 1_Development and validation of an endoscopic diagnostic model for sessile serrated lesions based on machine learning algorithms.docx by Xinying Yu (16400811)

“…SHapley Additive exPlanations (SHAP) for model contribution were plotted, and the model results were interpreted by calculating the contribution of each feature to the prediction results.…”

Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

“…<p>A model-based approach is developed for clustering categorical data with no natural ordering. …”

Risk element category diagram. by Yao Hu (3479972)

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Pseudocode for the missForestPredict algorithm. by Elena Albu (15181070)

Subjects: “…missforest imputation algorithm…”

The learning curve of each machine learning prediction model. by Jingru Dong (14076094)

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Partial dependence plots (A – G) and the resulting clustered feature importance (H) for each feature and trained model. by Daniel Walke (21680915)

“…In H), we hierarchically clustered (Euclidean distance with average linking) the feature importance resulting from the normalized variance in the partial dependence plots for each trained model. Tree-based algorithms (i.e., Decision Tree, Random Forest, XGBoost, and RUSBoost) are grouped together indicating similar underlying mechanisms for the classification. …”

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

Comparison of Point Cloud rigid registration algorithms. by Morena Raiola (22439390)