US 12,437,220 B2
Combined classical/quantum predictor evaluation with model accuracy adjustment
Aaron K. Baughman, Cary, NC (US); Gururaja Hebbar, Frisco, TX (US); Micah Forster, Round Rock, TX (US); Kavitha Hassan Yogaraj, Bangalore (IN); and Yoshika Chhabra, Gurgaon (IN)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on May 20, 2024, as Appl. No. 18/668,666.
Application 18/668,666 is a continuation of application No. 17/410,553, filed on Aug. 24, 2021, granted, now 12,061,952.
Prior Publication US 2024/0303518 A1, Sep. 12, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 15/16 (2006.01); G06F 40/20 (2020.01); G06N 10/00 (2022.01)
CPC G06N 10/00 (2019.01) [G06F 15/16 (2013.01); G06F 40/20 (2020.01)] 25 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
scoring, using a classical data model executing on a classical processor, a set of classical features, a classical feature in the set of classical features comprising a first attribute of a resource, a score of the classical feature comprising an evaluation of a utility of the classical feature in predicting a result involving the resource, the scoring resulting a scored set of classical features;
scoring, using a quantum data model executing on a quantum processor and a feature group selected from the scored set of classical features, a set of quantum features, a quantum feature in the set of quantum features comprising a second attribute of the resource, a score of the quantum feature comprising an evaluation of a utility of the quantum feature in predicting the result, the scoring resulting a scored set of quantum features;
combining, forming a combined set of scored features, the scored set of classical features and the scored set of quantum features; and
calculating, using the combined set of scored features and a first set of input data of the resource, the result involving the resource.