interpret and AIX360

interpret

Verified

AIX360

Established

Maintenance 25/25

Adoption 10/25

Maturity 16/25

Community 21/25

Maintenance 0/25

Adoption 18/25

Maturity 18/25

Community 24/25

Stars: 6,813

Forks: 778

Downloads: —

Commits (30d): 74

Language: C++

License: MIT

Stars: 1,767

Forks: 328

Downloads: 2,192

Commits (30d): 0

Language: Python

License: Apache-2.0

No Package No Dependents

Stale 6m

About interpret

interpretml/interpret

Fit interpretable models. Explain blackbox machine learning.

Combines glassbox models (EBM, decision trees, linear models) with post-hoc explainers (SHAP, LIME, partial dependence) in a unified API. Features Explainable Boosting Machines that match state-of-the-art blackbox performance while remaining fully interpretable with automatic interaction detection and differential privacy support. Integrates with scikit-learn ecosystems and provides Plotly/Dash-based dashboards for both global and local explanations across multiple models.

About AIX360

Trusted-AI/AIX360

Interpretability and explainability of data and machine learning models

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