Rule Extraction in Unsupervised Anomaly Detection for Model Explainability: Application to OneClass SVM

This paper evaluates some of the most important rule extraction techniques over OneClass SVM models, as well as presenting alternative designs for some of those XAI algorithms, and proposes algorithms to compute metrics related with XAI regarding the "comprehensivility", "representativeness", "stability" and "diversity" of the rules extracted.