Iteration curve of the optimization process. by Meijun Shang (22806461)

Reducing positional uncertainty by He Wu (22584128)

ROC curves. by Nicola Lazzarini (3528197)

PR curves. by Nicola Lazzarini (3528197)

Optimized model prediction performance. by Guang Tu (22054865)

Calibration plot of the apparent and optimism-corrected models. by Dominika Szabo (14129304)

Architecture of proposed system model. by Nanavath Kiran Singh Nayak (22184565)

System model of the proposed method. by Nanavath Kiran Singh Nayak (22184565)

ROC curve of six impact indicators. by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”

Analysis of CM1 ROC curve. by Mohd Mustaqeem (19106494)

Analysis PC2 AU-ROC curve. by Mohd Mustaqeem (19106494)

Analysis PC1 AU-ROC curve. by Mohd Mustaqeem (19106494)

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

Comparison of the four models. by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”

The robustness test results of the model. by Xini Fang (20861990)

“…Finally, an improved RF model is constructed by optimizing the parameters of the RF algorithm. …”

Set of variables VS model performance. by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”

Study design. by Maxence Coulombe (17921106)

“…At the delivery stage, all patients will receive both a Providence-type brace optimized by the semi-automatic algorithm leveraging a patient-specific FEM (Test) and a conventional Providence-type brace (Control), both designed using CAD/CAM methods. …”

Table_1_Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation.docx by Jiajin He (13386702)

S1 Code - by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”

S1 Data - by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”