Scala: Guide for Data Science Professionals

Anomaly detection with one-class SVC

The design of the one-class SVC is an extension of the binary SVC. The main difference is that a single class contains most of the baseline (or normal) observations and the other class is replaced by a reference point known as the SVC origin. The outliers (or abnormal) observations reside beyond (or outside) the support vector of the single class:

Illustration of the one-class SVC

The outlier observations have a labeled value of -1, while the remaining training sets are labeled +1. In order to create a relevant test, we add four more companies that have drastically cut their dividends (ticker symbols WLT, RGS, ...