Bar chart of feature importance for multiple datasets based on LIME. by Lang Deng (5681033)

Steps involved in genetic algorithm for feature selection. by Mohd Sakib (20565228)

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Summary of the feature selection algorithms. by Martin Kostadinov (20410120)

Comparative prediction performance analysis of different algorithms. by Dongqing Zhang (423941)

Feature selection using Boruta algorithm. by Shayla Naznin (13014015)

“…Feature selection was performed using the Boruta algorithm and model performance was evaluated by comparing accuracy, precision, recall, F1 score, MCC, Cohen’s Kappa and AUROC.…”

Comparison of the top 10 most important features. by Mengjiao Yin (10995604)

Algorithm performance in different operational phases. by Dongqing Zhang (423941)

Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms by Guangyin Jia (21075537)

“…By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. …”

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

Box plot the selected feature for weekends and weekdays in the dataset. by Mohd Sakib (20565228)

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The frequency of MRGs observed in the 113 algorithm combinations(A). by Xuefen Lin (17785367)

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Structure of GRU-CNN feature extraction network. by Qingling Zhang (758713)

The AUC of each model was calculated using 113 ML algorithm. by Xuefen Lin (17785367)

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Comparison of clinical features and MRG-related signature. by Xuefen Lin (17785367)

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Model results with temporal features. by Qun Zhao (603175)

The construction process of the CGO prediction model. by Wenbing Shi (5806160)

The comparison of different prediction methods on the test set. by Wenbing Shi (5806160)

Features of 13 pSRGs obtained by machine learning methods. by Xihao Shen (20347942)

Actual vs predicted net demand for all three models. by Mohd Sakib (20565228)

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Global and local feature (predictor variable) explanations from the XGBoost trained with Quebec data (2014–2021). by Hamid Ghanbari (6821096)