TRAINING A CLASSIFIER USED TO DETECT NETWORK ANOMALIES WITH SUPERVISED LEARNING

摘要

In one embodiment, a service receives relevancy feedback regarding anomalies detected in a network by one or more unsupervised learning-based anomaly detectors. The service generates a set of rules based on those of the anomalies deemed relevant by the relevancy feedback. The service uses the set of rules to trigger collection of data features from the network. The service trains a supervised learning-based classifier using the data features collected from the network.