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

21 Nov 2019Alberto BarbadoÓscar CorchoRichard Benjamins

OneClass SVM is a popular method for unsupervised anomaly detection. As many other methods, it suffers from the \textit{black box} problem: it is difficult to justify, in an intuitive and simple manner, why the decision frontier is identifying data points as anomalous or non anomalous... (read more)

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