I need to decide between SVM (One-Class Support Vector Machine) and PCA (PCA-Based Anomaly Detection) as anomaly detection methods. Azure ML is used and provides SVM and PCA as methods - hence the choice of 2 possible methods.
Does anyone have suggestions or a defined process for method selection? (Similar to cheat sheets you get for selecting a regression method).
The use case is to detect anomalies in high frequency network traffic data (from firewalls, routers & switches)?