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. A reference point, known as the SVC origin, replaces the second class. The outliers (or abnormal) observations reside beyond (or outside) the support vector of the single class:
The visualization 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, MDC, ...
Get Scala for Machine Learning now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
