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Descriptive analysis—part 1. (A): models, (B): data source, (C): type of data, (D): number of covariates. Extreme Gradient Boosting (XGB), Water Wave Optimization (WWO), Support Vector Machine (SVM), Inspired Modification of Partial Least Square (SIMPLS), SEKPS-CL, Random Forest (RF), Neural Network (NN), Naive Bayes (NB), Logistic Regression (LR), Linear Discriminant Analysis (LDA), Ensemble, Decision Tree (DT), Disease Risk Score.
