A toolbox to iNNvestigate neural networks' predictions!
This repository contains a sample implementation of Gradient Feature Auditing (GFA) meant to be generalizable to most datasets. For more information on the repair process, see our paper on Certifying and Removing Disparate Impact. For information on the full auditing process, see our paper on…
Project Page // Paper // No-code Web Demo // Colab Notebook
A model-agnostic tool for explaining machine learning models using rule surrogate and matrix-style visualization.
The main features of rulematrix/rule-matrix-py are: Explainable AI Libraries.
Open-source alternatives to rulematrix/rule-matrix-py include: albermax/innvestigate — A toolbox to iNNvestigate neural networks' predictions! algofairness/blackboxauditing — This repository contains a sample implementation of Gradient Feature Auditing (GFA) meant to be generalizable to most… alvinwan/neural-backed-decision-trees — Project Page // Paper // No-code Web Demo // Colab Notebook. andosa/treeinterpreter — TreeInterpreter. ankurtaly/integrated-gradients — (a.k.a. Path-Integrated Gradients, a.k.a. Axiomatic Attribution for Deep Networks). aerdem4/lofo-importance — Leave One Feature Out Importance.