MLwrap: An R package for simplifying Machine Learning Models

Dear R-packages community,

I am prof. Albert Ses? 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 Ses?
University of the Balearic Islands (UIB)
Department of Psychology
albert.sese at uib.es