Model-agnostic feature importance with python.
-
Updated
Mar 17, 2026 - Jupyter Notebook
#
pfi
Here are 4 public repositories matching this topic...
This project applies Explainable AI techniques to a Student Dropout dataset, covering pre-, in- and post-modeling explanations, as well as an analysis of their quality. The project was developed for the "Adavnced Topics on Machine Learning" course. 1st Semester of the 1st Year of the Master's Degree in Artificial Intelligence.
prototype anchors xgboost pca mlp tsne decision-tree lime xai surrogate-models criticism shap pfi faithfulness
-
Updated
Dec 16, 2025 - Jupyter Notebook
📊 SHAP Values and Other Indicators of Feature Predictive Power in Binary Classification 🧠
-
Updated
Feb 28, 2026 - Jupyter Notebook
Improve this page
Add a description, image, and links to the pfi topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the pfi topic, visit your repo's landing page and select "manage topics."