Advanced statistical modeling techniques for ensemble learning, specifically tailored to the analysis of lymphocyte counts and viral load data in the context of HIV research. Empowering researchers and practitioners, this tool provides a comprehensive solution for tasks such as analysis, prediction and risk calculation related to key viral metrics. The package incorporates cutting-edge ensemble learning principles, inspired by model stacking techniques of Simon P. Couch and Max Kuhn (2022)
Advanced statistical modeling techniques for ensemble learning, specifically focusing on CD4 lymphocytes counts and viral load data in the context of HIV research. This tool is tailored to empower researchers and practitioners in the field, offering a comprehensive solution for the analysis, prediction, and generation of risk calculations related to key HIV-related metrics. The package incorporates cutting-edge ensemble learning principles, drawing inspiration from model stacking techniques and in alignment with tidy data principles providing a robust and reproducible framework for HIV research.