US 12,287,718 B2
Short-term model calibration in system monitoring
Nigel Slinger, Los Gatos, CA (US); Wenjie Zhu, Dublin (IE); Catherine Drummond, Morgan Hill, CA (US); and Sudipta Sengupta, Richmond, TX (US)
Assigned to BMC Software, Inc., Houston, TX (US)
Filed by BMC Software, Inc., Houston, TX (US)
Filed on Mar. 26, 2021, as Appl. No. 17/301,143.
Prior Publication US 2022/0308977 A1, Sep. 29, 2022
Int. Cl. G06F 11/34 (2006.01); G06N 20/00 (2019.01); G06Q 10/0639 (2023.01)
CPC G06F 11/3428 (2013.01) [G06N 20/00 (2019.01); G06Q 10/0639 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instructions that, when executed by at least one computing device, are configured to cause the at least one computing device to:
detect a calibration trigger for a technology landscape, the technology landscape being characterized using a performance characterization that includes scores assigned to performance metrics for the technology landscape and using at least one trained machine learning model;
determine, in response to the calibration trigger, a calibratable performance metric of the performance metrics;
determine a relationship between conforming values of the calibratable performance metric during a conforming period for which the at least one trained machine learning model was trained, and non-conforming values of the calibratable performance metric occurring during a calibration period initiated by the calibration trigger; and
calibrate a score assigned to the calibratable performance metric by the at least one trained machine learning model during the calibration period, based on the relationship, to thereby obtain a calibrated score for inclusion in the performance characterization.