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Explainable machine learning with mlr3 and DALEX

Przemysław Biecek and Szymon Maksymiuk added a new chapter to the mlr3 book on how to analyze machine learning models fitted with mlr3 using the excellent DALEX package.

The contributed chapter covers an analysis of a random regression forest (implemented in the ranger package) on data extracted from the FIFA video game. In more detail, the following methods for explainable machine learning are showcased:

  • Dataset level exploration: Feature importance and Partial dependency plots.
  • Instance level explanation: Break Down, SHapley Additive exPlanations (SHAP), and Ceteris Paribus plots.

Here is a small preview illustrating the effect of different features on the monetary value of Cristiano Ronaldo:

Read the complete chapter here.