The project involves data preprocessing, visualization of outliers, model training, and evaluation using cross-validation.
The performance of individual models, such as Random Forest, GLMNet, and XGBoost, is assessed, and their variable importance is analyzed.
The combined model's accuracy is evaluated and compared to the base models.
Copyright 2024 Mattia Bennati
Licensed under the GNU GPL V2: https://www.gnu.org/licenses/old-licenses/gpl-2.0.html