Opening the Black Box: Interpreting Machine Learning Models with SHAP Values in R

Hands-on tutorial given at uRos2026 (Use of R in Official Statistics), Paris, 18 November 2026: interpreting machine learning models with SHAP values in R.

Keywords

SHAP, Interpretable machine learning, R, uRos2026

Opening the Black Box: Interpreting Machine Learning Models with SHAP Values in R

Hands-on tutorial given at uRos2026 (Use of R in Official Statistics), Paris, 18 November 2026.

Work in progress.

The tutorial website hosts the slides, the course notes and the setup guide. The GitHub repository contains what you need to code along: the exercise script, the trained model, the data, a demo Shiny app and the pinned R environment.

Prerequisites: intermediate R, tidyverse, basic ML concepts (train/test split, model fitting). No prior knowledge of SHAP is required.

Tutorial website

GitHub repository

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