Search Packages

shapash

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

visualime

Implementation of LIME focused on producing user-centric local explanations for image classifiers.

covidxai

Implementation of explainability algorithms (layer-wise relevance propagation, local interpretable model-agnostic explanations, gradient-weighted class activation mapping) on computer vision architectures to identify and explain regions of COVID 19 pneumonia in chest X-ray and CT scans.

xfin-xai

Privacy-Preserving Explainable AI Library for Financial Services and Banking Systems

tic

TIC is a library that acts as a Toolbox for Interpretability Comparison.

aizenx-xai

AizenX - Explainable AI toolkit for model interpretability and fairness

impl

LIME-based library for interpretation of local models

xwhy

Explaining black boxes with a SMILE: Statistical Mode-agnostic Interpretability with Local Explanations