Skip to main content

AXA SAFE AI package to measure risks of CatBoost models

Project description

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:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

axa_safeai-0.1.4.tar.gz (9.3 kB view details)

Uploaded Source

File details

Details for the file axa_safeai-0.1.4.tar.gz.

File metadata

  • Download URL: axa_safeai-0.1.4.tar.gz
  • Upload date:
  • Size: 9.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for axa_safeai-0.1.4.tar.gz
Algorithm Hash digest
SHA256 8faf95c600e2d2c8fc94f006564dcbc6bb24432e4bba888241505d149a7a3901
MD5 005cc3b2531a0fc76d5a3871b8c12b23
BLAKE2b-256 68e649f99558b5993ee4d5671c3c2593b84d5c8679faed4626f63b34f32fc3f5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page