Description and frequency of the Features in the case and control groups. حسب Faten Al-hussein (20707521)

Description of the dataset features. حسب Wan-Hua Zhang (21601139)

Proposed feature sets and description. حسب Arta Misini (19929042)

Description of features. حسب Sadia Nazim (21440115)

Description of dependent variable or feature. حسب Mst. Rokeya Khatun (22226685)

"…Logistic regression was applied to identify statistically significant predictors of school dropout. ML algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGB), were used to build predictive models. …"

Description of the datasets. حسب Chenyi Zhu (9383370)

Structure description of the eight datasets. حسب Jia Liu (41593)

Policy intervention descriptions. حسب Zachary J. Ward (10126662)

The brief description on the WTCCC dataset. حسب Liyan Sun (760586)

Statistical description of datasets. حسب Varun Malik (21212874)

A collection of visual features and their extremes. حسب Hector Torres (11708207)

Countplot for categorical features. حسب Mst. Rokeya Khatun (22226685)

"…Logistic regression was applied to identify statistically significant predictors of school dropout. ML algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGB), were used to build predictive models. …"

Violin plot for numerical feature age. حسب Mst. Rokeya Khatun (22226685)

"…Logistic regression was applied to identify statistically significant predictors of school dropout. ML algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGB), were used to build predictive models. …"

Illustrations of psychophysical experiment interface. حسب Chenxi Liao (5622617)

Workflow summary: GRN motif, cell signaling model, and inference framework. حسب Michael Alexander Ramirez Sierra (20209354)

XGB 10-Fold Cross-Validation. حسب Mst. Rokeya Khatun (22226685)

"…Logistic regression was applied to identify statistically significant predictors of school dropout. ML algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGB), were used to build predictive models. …"

Confusion matrix. حسب Mst. Rokeya Khatun (22226685)

"…Logistic regression was applied to identify statistically significant predictors of school dropout. ML algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGB), were used to build predictive models. …"

AUC-ROC curve for different ML models. حسب Mst. Rokeya Khatun (22226685)

"…Logistic regression was applied to identify statistically significant predictors of school dropout. ML algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGB), were used to build predictive models. …"

VIF Scores Supporting Low Multicollinearity. حسب Mst. Rokeya Khatun (22226685)

"…Logistic regression was applied to identify statistically significant predictors of school dropout. ML algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGB), were used to build predictive models. …"

Underlying Data for '<b>Detection of False Position Attacks in VANETs through Bagging Ensemble Learning</b>' حسب Bekan Mekonen (21544637)