Forest (RF), Support Vector Regressor (SVR), K-Nearest Neighbor (KNN), and eXtreme Gradient Boosting (XGBoost) - were …

in the highest risk decile, capturing about 55% of cases, whereas linear models and Extreme Gradient Boosting excel in …This study employs six Machine Learning methods - Logit, Lasso-Logit, Ridge-Logit, Random Forest, Extreme Gradient … Boosting, and an Ensemble - alongside registry data on abortions in Spain from 2011-2019 to predict multiple abortions and …

oversampling technique and compared the results. It was found that random forest and extreme gradient-boosting decision trees are …

oversampling technique and compared the results. It was found that random forest and extreme gradient-boosting decision trees are …

to comprehensively assess predictive performance. For frequency prediction, extreme gradient boosting (XGBoost … slightly higher MAE. For severity prediction, extreme gradient boosting (XGBoost) displays the lowest MAE, implying better … error magnitudes despite a higher MAE. In conclusion, extreme gradient boosting (XGBoost) stands out in mean absolute error …

in the highest risk decile, capturing about 55% of cases, whereas linear models and Extreme Gradient Boosting excel in …This study employs six Machine Learning methods - Logit, Lasso-Logit, Ridge-Logit, Random Forest, Extreme Gradient … Boosting, and an Ensemble - alongside registry data on abortions in Spain from 2011-2019 to predict multiple abortions and …

) approach, which selects the most important attributes. Logistic Regression (LR), K-Nearest Neighbors (KNN), Extreme Gradient … Boosting (XGB), Gradient Boosting (GB), Random Forest (RF), Multilayer Perceptron (MLP), and Support Vector Machine (SVM …