Patent ID: 11887012
Assignee: SAS INSTITUTE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. A method of identifying an anomaly among a plurality of observation vectors, the method comprising:
training, by a computing device, a machine learning model by
executing a robust principal components algorithm with a plurality of training observation vectors to compute a low-rank matrix;
decomposing the low-rank matrix;
determining a rank of the low-rank matrix;
determining an orthogonal complement matrix using the decomposed low-rank matrix and the determined rank;
projecting each observation vector of the plurality of training observation vectors using the determined orthogonal complement matrix; and
executing an independent component analysis algorithm with the projected plurality of training observation vectors to define a demixing matrix; and

applying, by the computing device, the trained machine learning model by
projecting, by the computing device, an observation vector using the determined orthogonal complement matrix;
multiplying, by the computing device, the projected observation vector by the defined demixing matrix to define a demixed observation vector;
computing, by the computing device, a detection statistic value from the defined, demixed observation vector; and
when the computed detection statistic value is greater than or equal to a predefined anomaly threshold value, outputting, by the computing device, an indicator that the observation vector is an anomaly.