Trusted-AI / AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
☆2,409Updated 2 months ago
Related projects: ⓘ
- Interpretability and explainability of data and machine learning models☆1,610Updated 2 months ago
- A Python package to assess and improve fairness of machine learning models.☆1,907Updated last week
- Bias Auditing & Fair ML Toolkit☆670Updated last week
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,335Updated 5 months ago
- Fit interpretable models. Explain blackbox machine learning.☆6,218Updated this week
- XAI - An eXplainability toolbox for machine learning☆1,098Updated 2 years ago
- Algorithms for explaining machine learning models☆2,383Updated 2 months ago
- A curated list of awesome responsible machine learning resources.☆3,586Updated last week
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆2,752Updated 2 years ago
- Source code/webpage/demos for the What-If Tool☆905Updated last week
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,364Updated last month
- Code for "High-Precision Model-Agnostic Explanations" paper☆794Updated 2 years ago
- Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable …☆1,327Updated last month
- ☆1,070Updated this week
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆816Updated 2 years ago
- Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world d…☆417Updated 3 months ago
- Algorithms for outlier, adversarial and drift detection☆2,206Updated last month
- Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …☆673Updated 3 months ago
- Library for Semi-Automated Data Science☆328Updated this week
- python partial dependence plot toolbox☆840Updated 2 weeks ago
- 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models☆2,713Updated last week
- ☆903Updated last year
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,211Updated 2 months ago
- OmniXAI: A Library for eXplainable AI☆861Updated last month
- H2O.ai Machine Learning Interpretability Resources☆481Updated 3 years ago
- A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.☆3,851Updated last week
- This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and b…☆1,245Updated last month
- A collection of research materials on explainable AI/ML☆1,385Updated last month
- ☆311Updated last year
- ☆359Updated 3 years ago