https://github.com/explainx/explainx

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms8909@nyu.edu

aws-sagemaker bias blackbox explainability explainable-ai explainable-artificial-intelligence explainable-ml explainx interpretability interpretable-ai interpretable-machine-learning machine-learning machine-learning-interpretability scikit-learn transparency xai

Last synced: 16 May 2025

https://github.com/explainX/explainx

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms8909@nyu.edu

aws-sagemaker bias blackbox explainability explainable-ai explainable-artificial-intelligence explainable-ml explainx interpretability interpretable-ai interpretable-machine-learning machine-learning machine-learning-interpretability scikit-learn transparency xai

Last synced: 04 Apr 2025

https://github.com/explainx/visual-counterfactuals

A visual counterfactual explanation of predictions by machine learning models. Work adapted from https://arxiv.org/abs/2003.02428.

Last synced: 16 Dec 2025

https://github.com/explainx/surrogate-rule-exploration-method

Easily explain the behavior of machine learning models using decision rules generated by decision trees. Work adapted from https://github.com/nyuvis/SuRE

Last synced: 24 Dec 2025