LARGE-SCALE ANOMALY DETECTION WITH RELATIVE DENSITY-RATIO ESTIMATION

摘要

In one embodiment, a set of training data consisting of inliers may be obtained. A supervised classification model may be trained using the set of training data to identify outliers. The supervised classification model may be applied to generate an anomaly score for a data point. It may be determined whether the data point is an outlier based, at least in part, upon the anomaly score.