BCG-X-Official/facet

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Interpretability and explainability of data and machine learning models

A game theoretic approach to explain the output of any machine learning model.

Fit interpretable models. Explain blackbox machine learning.

Deep Insight And Neural Network Analysis

Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world datasets and workflows.

Source code/webpage/demos for the What-If Tool

TrustyAI Explainability Toolkit

Lime: Explaining the predictions of any machine learning classifier