pfi

Model-agnostic feature importance with python.

Modèle LaTeX officiel rapport de stage PFA & PFE ingénieur Maroc (ENSAF, réseau ENSA, écoles d'ingénieurs). Génération Word/PDF 1-clic, linter académique automatique (lint.py), prêt pour Overleaf & assistants IA.

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.

Reference implementation of VFMcalc API. Licensed under BSL 1.1 (Not Open Source for production). Official paid service will be available soon!

📊 SHAP Values and Other Indicators of Feature Predictive Power in Binary Classification 🧠