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viruslearner

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.

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Install

install.packages('viruslearner')

Monthly Downloads

3

Version

0.0.2

License

MIT + file LICENSE

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Maintainer

Juan Pablo Acuña González

Last Published

April 3rd, 2024

Functions in viruslearner (0.0.2)

viruslearner-package

viruslearner: Ensemble Learning for HIV-Related Metrics
cd_ens

CD4 Cell Count or Viral Load Ensemble Learning Through Stacking of Models.
cd_fit

Fit and Evaluate Stacked Ensemble Model for CD4 Cell Count or Viral Load Outcome
cd_stack

CD4 Cell Count or Viral Load Plot of Blending Coefficients for the Stacking Ensemble
vl_test

Viral Rates Dataset for Testing Viral Load Outcome
vl_train

Viral Rates Dataset for Training Viral Load Outcome
viralrates

Viral Rates Dataset
viral_new

Viral New Dataset
mortality

Mortality Dataset
cd_train

Viral Rates Dataset for Training CD4 Counts Outcome
cd_test

Viral Rates Dataset for Testing CD4 Counts Outcome