Published January 30, 2023 | Version v1
Software Open

AXOM - Combination of Weak Learners eXplanations to Improve Random Forest eXplicability Robustness (Source Code)

  • 1. Universidad Politécnica de Madrid
  • 2. Artificial Intelligent Department, Universidad Politécnica de Madrid

Description

This entry includes all the code and data used in the paper  'Combination of Weak Learners eXplanations to Improve Random Forest eXplicability Robustness'. The code is programmed in Python language. It includes the functions for the robustness assessment of the method AXOM and, also all the code used to create the plots of the paper. The file README.md describes briefly how to use it to reproduce the paper results. 

The use os this code is licencse under CC-by-author and you may use it freely at your own risk.

Notes

None.

Files

AXOM-srcCode.zip

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