Supplementary Data for "Visualizing the Explainability and Robustness of Machine Learning Models through Fitting Graphs"

This repository contains the supplementary materials accompanying the article“Visualizing the Explainability and Robustness of Machine Learning Models through Fitting Graphs”, submitted to Applied Artificial Intelligence. The datasets demonstrate the use of fitting graphs, a novel visualization technique designed to help model developers evaluate and interpret machine learning models in terms of explainability and robustness. The materials include: Real-world datasets (e.g., Baseball, Boston Housing, and Parkinson’s datasets) The data used to generate all the original figures in the article These resources support transparency and reproducibility for the analyses presented in the paper.