Genetic algorithm flowchart. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

The Search process of the genetic algorithm. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Genetic algorithm iteration data chart. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Image_1_Uncovering the Achilles heel of genetic heterogeneity: machine learning-based classification and immunological properties of necroptosis clusters in Alzheimer’s disease.TIF... by Huangwei Wei (17011266)

“…Background<p>Alzheimer’s disease (AD) is an age-associated neurodegenerative disease, and the currently available diagnostic modalities and therapeutic agents are unsatisfactory due to its high clinical heterogeneity. …”

Table_1_Uncovering the Achilles heel of genetic heterogeneity: machine learning-based classification and immunological properties of necroptosis clusters in Alzheimer’s disease.XLS... by Huangwei Wei (17011266)

“…Background<p>Alzheimer’s disease (AD) is an age-associated neurodegenerative disease, and the currently available diagnostic modalities and therapeutic agents are unsatisfactory due to its high clinical heterogeneity. …”

Image_2_Uncovering the Achilles heel of genetic heterogeneity: machine learning-based classification and immunological properties of necroptosis clusters in Alzheimer’s disease.TIF... by Huangwei Wei (17011266)

“…Background<p>Alzheimer’s disease (AD) is an age-associated neurodegenerative disease, and the currently available diagnostic modalities and therapeutic agents are unsatisfactory due to its high clinical heterogeneity. …”

Bias-variance decomposition of the Mean Squared Error (MSE). by Konstantina Charmpi (9901053)

S1 File - by Xihao Shen (20347942)

“…A cluster analysis of rejection samples was conducted using the consensus clustering algorithm. …”

6 data sets included in this study. by Xihao Shen (20347942)

“…A cluster analysis of rejection samples was conducted using the consensus clustering algorithm. …”

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)

Technical approach. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Data set presentation. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Pearson correlation coefficient matrix plot. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

SHAP of stacking. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Demonstration of data imbalance. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Stacking ROC curve chart. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Confusion matrix. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

GA-XGBoost feature importances. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Partial results of the chi-square test. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Stacking confusion matrix. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”