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

Regression, Gradient Boosting Regression, Random Forest Regression, Polynomial Regression, and Decision Tree Regression. The …

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

. This paper implements an outlier-based error-spotting algorithm using gradient boosting, and presents a blueprint for the … Bank of Hungary (MNB), and introduces a set of synthetic error types to test its hypotheses. The paper shows that gradient … boosting is not materially impacted by the choice of the imputation method, hence, replacement with a constant, the …

the predictive performance of Gradient Boosting with decision trees as base learners to model the claim frequency and the …. The out-of-sample performance measure results show that the predictive performance of the Gradient Boosting Model (GBM) is … classical GLM outperformed the Gradient Boosting Model. The findings suggest that gradient boost models can capture the non …

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