Sample images from the BreakHis dataset. by Afnan M. Alhassan (18349378)

Weights of sample data. by Yixuan Lu (9987980)

Sample data of K-means clustering. by Yixuan Lu (9987980)

Parameter settings. by Yang Cao (53545)

“…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …”

Reducing positional uncertainty by He Wu (22584128)

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

Optimal Timings Codebook.xlsx by Emma Spillane (11249121)

Bootstrap results for Case 1. by Muhammad Hamza (798822)

“…Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. …”

Flow diagram of DGCART. by Muhammad Hamza (798822)

“…Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. …”

Bootstrap results Case 2. by Muhammad Hamza (798822)

“…Regression models, on one side, optimize the prediction of the study variable’s non-sampled values while the classification algorithms, on the other side, look for the classification of non-sampled cases into different strata. …”

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

“…<div><p>To enhance the accuracy and response speed of the risk early warning system, this study develops a novel early warning system that combines the Fuzzy C-Means (FCM) clustering algorithm and the Random Forest (RF) model. Firstly, based on operational risk theory, market risk, research and development risk, financial risk, and human resource risk are selected as the primary indicators for enterprise risk assessment. …”

Construction process of RF. by Xini Fang (20861990)

“…<div><p>To enhance the accuracy and response speed of the risk early warning system, this study develops a novel early warning system that combines the Fuzzy C-Means (FCM) clustering algorithm and the Random Forest (RF) model. Firstly, based on operational risk theory, market risk, research and development risk, financial risk, and human resource risk are selected as the primary indicators for enterprise risk assessment. …”

Supplementary file 1_Development of a venous thromboembolism risk prediction model for patients with primary membranous nephropathy based on machine learning.docx by Lian Li (49049)

“…Among the 504 models constructed, the NGBoost model, which incorporated imputation by K-Nearest Neighbor, sampling by Borderline-SMOTE, and feature selection by Frequency-based Selection, was identified as the optimal model, achieving an area under the curve (AUC) of 0.911. …”

Demographics. by Sachin V. Trivedi (19500738)

“…Participants completed one, or both, of an algorithm generated self-triage (AGST) survey, or visual acuity scale (VAS) based self-triage tool which subsequently generated a CTAS score. …”

VAS triage tool vs. nurse-driven triage. by Sachin V. Trivedi (19500738)

“…Participants completed one, or both, of an algorithm generated self-triage (AGST) survey, or visual acuity scale (VAS) based self-triage tool which subsequently generated a CTAS score. …”

AGST tool vs. nurse-driven triage. by Sachin V. Trivedi (19500738)

“…Participants completed one, or both, of an algorithm generated self-triage (AGST) survey, or visual acuity scale (VAS) based self-triage tool which subsequently generated a CTAS score. …”

AGST survey questions. by Sachin V. Trivedi (19500738)

“…Participants completed one, or both, of an algorithm generated self-triage (AGST) survey, or visual acuity scale (VAS) based self-triage tool which subsequently generated a CTAS score. …”

primary ATRT single cell RNA-seq by Mamy ANDRIANTERANAGNA (12913196)

Optimal Time Intervals of Breech Births Dataset by Emma Spillane (11249121)

Table_1_Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma.docx by Jiang Zhu (40858)