title: Any anomaly detection algorithm does not require pre-determined anomaly percentage?
body: <p>Most common anomaly detection algorithms that I know of (e.g., OneClass SVM) require that one estimates the percentage of anomalies in the dataset; e.g., 1%, o.1%, etc. Then it lists the top 1% (or 0.1%, etc.) highest scores from the output and classify them as anomalies. In some situations, one may not be able to accurately estimate the percentage.</p>
  
  <p>Are there algorithms that do not require pre-determined anomaly ratios?</p>