Anomaly detection

Anomaly detection, as the name implies, looks for unexpected events in the data submitted to the model. Data for this algorithm, as you can probably guess, requires data over a period of time. Anomaly detection in ML.NET looks at both spikes and change points. Spikes, as the name implies, are temporary, whereas change points are the starting points of a longer change.

ML.NET provides an anomaly detection algorithm, which we will cover in Chapter 6, Anomaly Detection Model.