Open leonardobegher opened 6 years ago
Hi, The network is trained in an unsupervised manner; Therefore, the labels are not used for training. However, They are needed to evaluate the performance of the network. When evaluating the performance of the network, we need to calculate the accuracy of the anomaly detection using F-1 metrics which requires the truth labels.
The anomaly detector is really awesome! I want to know, if there is a way to adapt it, to detect anomalies without labeling the data, like the unsupervised learning. Thanks!