A OneClassSVM object stores a one-class support vector machine fitted to a set of observations in an expanded feature space, and detects anomalies through the isanomaly method. Create a model with the ocsvm function rather than by calling this constructor directly.

The model maps the data to a randomized feature space that approximates a Gaussian kernel and fits a linear boundary that encloses the bulk of the observations; points outside the boundary receive higher anomaly scores.

See also: ocsvm, isanomaly

Source Code: OneClassSVM