axa-safeai 0.2.2

AXA SAFE AI package to measure accuracy, explainability, fairness and robustness of any classification and regression model.

AXA safeAI package

This S.A.F.E. approach is based on “Rank Graduation Box” proposed in Babaei et al. 2024. The use of the term “box” is motivated by the need of emphasizing that our proposal is always in progress so that, like a box, it can be constantly filled by innovative tools addressed to the measurement of the new future requirements necessary for the safety condition of AI-systems.

Install

Simply use:

pip install axa_safeai

Citations

The proposed measures in this package came primarily out of research by Paolo Giudici, Emanuela Raffinetti, and Golnoosh Babaei in the Statistical laboratory at the University of Pavia.

This package is based on the following papers:

• Babaei, G., Giudici, P., & Raffinetti, E. (2024). A Rank Graduation Box for SAFE AI. Expert Systems with Applications, 125239.
• Giudici, P., & Raffinetti, E. (2024). RGA: a unified measure of predictive accuracy. Advances in Data Analysis and Classification, 1-27.
• Raffinetti, E. (2023). A rank graduation accuracy measure to mitigate artificial intelligence risks. Quality & Quantity, 57(Suppl 2), 131-150.