Table 3 - حسب Muhammad Tayyab Zamir (20455240)

"…<p>Statistical performance indicators for machine learning algorithms in classification can be evaluated through (a) overall metrics and (b) classification based on macro and weighted indicators.…"

Methodological flowchart outlining the study’s workflow. حسب Ezekiel Ahn (6697256)

"…It proceeds through preprocessing, preliminary statistical analysis (including PCA and hierarchical clustering), and three primary machine learning tasks: cluster classification (using both undersampling and ADASYN oversampling), machine learning-based clustering, and grain yield prediction. …"

Passenger flow of Jinan Railway Bureau in 2019. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Relevant literature research content statistics. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Train timetable data. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Sample of train service network. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Notations definition table. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Calculation of passenger time value. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Chart of changes in passenger travel utility. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Abstracted train service network. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Passenger flow data. حسب Jiren CAO (20442214)

"…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …"

Immunogenicity profiles relate to acquisition status and can be used to infer protection status. حسب Shiwei Xu (9290764)

Machine Learning Modeling for ABC Transporter Efflux and Inhibition: Data Curation, Model Development, and New Compound Interaction Predictions حسب Nada J. Daood (18626266)

"…Quantitative structure–activity relationship (QSAR) models were developed for each of the eight data sets using combinations of four machine learning algorithms and three sets of chemical descriptors. The resulting models demonstrated excellent performance by 5-fold cross-validation, achieving an average correct classification rate (CCR) of 0.764 for the substrate binding models and 0.839 for the inhibition models. …"

Texture operators. حسب Antonio Quintero-Rincón (21087716)

"…This paper presents an algorithm and experimental results demonstrating the feasibility of developing automated tools to detect abnormal X-ray images based on tissue attenuation. …"

Multiclass—AUC ROC Curve for XGBoost model. حسب Sasja Maria Pedersen (11880264)

"…</p><p>Methods</p><p>We classify HbA1c test intervals into four categories (3, 6, 9, and 12 months) using three classification algorithms: logistic regression, random forest, and extreme gradient boosting (XGBoost). …"

Confusion matrix—XGBoost. حسب Sasja Maria Pedersen (11880264)

"…</p><p>Methods</p><p>We classify HbA1c test intervals into four categories (3, 6, 9, and 12 months) using three classification algorithms: logistic regression, random forest, and extreme gradient boosting (XGBoost). …"

Model information. حسب Sasja Maria Pedersen (11880264)

"…</p><p>Methods</p><p>We classify HbA1c test intervals into four categories (3, 6, 9, and 12 months) using three classification algorithms: logistic regression, random forest, and extreme gradient boosting (XGBoost). …"

Predictor variables. حسب Sasja Maria Pedersen (11880264)

"…</p><p>Methods</p><p>We classify HbA1c test intervals into four categories (3, 6, 9, and 12 months) using three classification algorithms: logistic regression, random forest, and extreme gradient boosting (XGBoost). …"

SHAP. حسب Sasja Maria Pedersen (11880264)

"…</p><p>Methods</p><p>We classify HbA1c test intervals into four categories (3, 6, 9, and 12 months) using three classification algorithms: logistic regression, random forest, and extreme gradient boosting (XGBoost). …"

Feature importance. حسب Sasja Maria Pedersen (11880264)

"…</p><p>Methods</p><p>We classify HbA1c test intervals into four categories (3, 6, 9, and 12 months) using three classification algorithms: logistic regression, random forest, and extreme gradient boosting (XGBoost). …"