Interpreting Machine Learning Predictions with SHAP and LIME for Transparent Decision Making
Machine learning models increasingly influence critical decisions across diverse domains, yet their complex architectures often operate as black boxes, obscuring the rationale behind predictions and limiting stakeholder trust. This research demonstrates a comprehensive, reproducible workflow for applying explainable ar...
M. Stow
· International Journal of Com... · 1 citation