Dear R-packages community,
I am prof. Albert Sesé from the University of the Balearic Islands (UIB).
I am writing to announce MLwrap, an R package now available on CRAN.
MLwrap is designed to simplify machine learning implementation for
educational and research contexts. It provides a step-by-step workflow
that emphasizes reproducibility, transparency, and pedagogical clarity.
The package integrates four machine learning algorithms:
- Neural Networks (Multilayer Perceptron)
- Support Vector Machines
- Random Forests
- XGBoost
Key features:
- Unified pipeline for model building, optimization, and evaluation
- Explicit handling of random seeds for reproducibility
- Clear, accessible interface for learning
- Built-in sensitivity analysis for model interpretation
Resources:
CRAN package: https://cran.r-project.org/web/packages/MLwrap
Tutorial: https://osf.io/preprints/psyarxiv/j6m4z
Web page: https://areademetodologia.uib.es/MLwrap/MLwrap_website.html
MLwrap is particularly useful for teaching statistics and data science
courses to students and researchers new to machine learning.
Best regards,
Dr. Albert Sesé
University of the Balearic Islands (UIB)
Department of Psychology
[email protected]
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