US 12,437,216 B2
Combined classical/quantum predictor evaluation
Aaron K. Baughman, Cary, NC (US); Souvik Mazumder, Kolkata (IN); Mohit Trivedi, Dunwoody, GA (US); Gururaja Hebbar, Frisco, TX (US); Daniel Joseph Fry, Buchare (RO); Kavitha Hassan Yogaraj, Bangalore (IN); and Herman Colquhoun, Markham (CA)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Jul. 6, 2021, as Appl. No. 17/367,899.
Prior Publication US 2023/0010615 A1, Jan. 12, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 5/04 (2023.01); G06F 15/16 (2006.01); G06F 40/20 (2020.01); G06N 10/60 (2022.01); G06N 20/20 (2019.01)
CPC G06N 5/04 (2013.01) [G06F 15/16 (2013.01); G06F 40/20 (2020.01); G06N 10/60 (2022.01); G06N 20/20 (2019.01)] 20 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;
scoring, using a quantum data model executing on a quantum processor and 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;
wherein scoring the quantum feature utilizes one of a Quantum Support Vector Machine (QSVM) and Quantum Approximate Optimization Algorithm (QAOA);
forming a combined set of scored features by correlating common features of 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 a resource, a valuation of the resource.