2 papers
cs.LG2025
Combining SHAP and Causal Analysis for Interpretable Fault Detection in Industrial Processes
Pedro Cortes dos Santos, Matheus Becali Rocha, Renato A Krohling
Industrial processes generate complex data that challenge fault detection systems, often yielding opaque or underwhelming results despite advanced machine learning techniques. This…
cs.LG2025
Enhancing Diagnostic Accuracy for Urinary Tract Disease through Explainable SHAP-Guided Feature Selection and Classification
Filipe Ferreira de Oliveira, Matheus Becali Rocha, Renato A. Krohling
In this paper, we propose an approach to support the diagnosis of urinary tract diseases, with a focus on bladder cancer, using SHAP (SHapley Additive exPlanations)-based feature s…