to comprehensively assess predictive performance. For frequency prediction, extreme gradient boosting (XGBoost …) demonstrates the lowest MAE, indicating higher accuracy compared to gradient boosting machines (GBMs) and a generalized linear … magnitudes compared to gradient boosting machines (GBMs) and a generalized linear model (Poisson). Conversely, the generalized …

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

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 …

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 …

Linear Model (GLM), Gradient Boosting Machine (GBM), Artificial Neural Networks (ANN), and a unique hybrid model that …