The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 03, 2026

Filed:

Jul. 26, 2022
Applicant:

Capital One Services, Llc, McLean, VA (US);

Inventors:

Samuel Sharpe, Cambridge, MA (US);

Christopher Bayan Bruss, Washington, DC (US);

Brian Barr, Schenectady, NY (US);

Sahil Verma, San Francisco, CA (US);

Jocelyn Huang, Purcellville, VA (US);

Assignee:

Capital One Services, LLC, McLean, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/045 (2023.01); G06F 11/34 (2006.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 5/045 (2013.01); G06F 11/3495 (2013.01); G06N 20/00 (2019.01);
Abstract

A computing system may generate a first set of importance metrics (e.g., scores or values) for a model. The importance metrics may be generated using an explainable artificial intelligence technique, and an individual importance metric may indicate how influential a corresponding feature is for a decision made by a model. The computing system may determine an important feature and create a modified dataset by removing the important feature from the dataset. The computing system may train the model on the modified dataset and evaluate the performance of the model to determine the effect of removing the feature (e.g., which may indicate how important the feature is to output generated by the model). This process may be repeated for additional features and additional performance metrics may be obtained.


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