Skip to content

Latest commit

 

History

History
17 lines (9 loc) · 1006 Bytes

README.md

File metadata and controls

17 lines (9 loc) · 1006 Bytes

Twin-Systems

This repository is to accompany the IJCAI-2019 publication:

"Twin-Systems to Explain Artificial Neural Networks using Case-Based Reasoning: Comparative Tests of Feature-Weighting Methods in ANN-CBR Twins for XAI"

https://www.ijcai.org/proceedings/2019/0376.pdf?fbclid=IwAR20s22C5x8DUj9EMMmL3Pw72nG5XPiyL2BiIpARvmmb4GSkCYSEBFEi9jQ

Everything necessary to recreate the paper is included above in three folders with iPython notebooks.

  1. Tabular with Sigmoid -- This is an example of twinning an MLP with a CBR system when using a Sigmoid output with tabular data in a binary class classification domain.

  2. Tabular with SoftMax -- This is an example of twinning an MLP with a CBR system when using a SoftMax output with tabular data in a multi-class classification domain.

  3. Deep Learning -- This is an example of twinning a CNN with a CBR system for image data in a classification domain.

Any questions or queries feel free to email me at [email protected] -- Thanks for reading!