Search Packages

optbinning

Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual explanations.

dice-ml

Generate Diverse Counterfactual Explanations for any machine learning model.

acfx

Actionable Counterfactual eXplanations

ceval

CEval is a Python package for evaluating the quality of counterfactual explanations produced by any post-hoc XAI (Explainable AI) method. It computes 14 established metrics with a single call and works with diverse model architecture.

cfnet

Recourse Explanation Library in JAX

carla-recourse

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

lux-explainer

Universal Local Rule-based Explainer

ceml

CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox

genfact

A model agnostic and gradient-free optimization method for generating counterfactuals

cfnow

Easiest way to generate counterfactual explanations

ellice

An efficient + provably robust implementation of algorithmic recourse via Rashomon sets in PyTorch & Scikit-Learn (NeurIPS '25 Spotlight)

gamcoach

Personal coach to help you obtain desired AI decisions!

aizenx-xai

AizenX - Explainable AI toolkit for model interpretability and fairness

xmoai

xMOAI 🗿

cfai

A collection of algorithms of counterfactual explanations.