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. 18, 2025

Filed:

Sep. 16, 2020
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Lukasz G. Cmielowski, Cracow, PL;

Wojciech Sobala, Cracow, PL;

Maksymilian Erazmus, Zasow, PL;

Rafal Bigaj, Cracow, PL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 18/21 (2023.01); G06F 17/15 (2006.01); G06F 17/18 (2006.01); G06N 3/08 (2023.01); G06N 3/09 (2023.01); G06N 20/00 (2019.01); G06V 10/766 (2022.01); G06V 10/776 (2022.01);
U.S. Cl.
CPC ...
G06F 18/217 (2023.01); G06F 17/15 (2013.01); G06F 17/18 (2013.01); G06N 3/08 (2013.01); G06N 3/09 (2023.01); G06N 20/00 (2019.01); G06V 10/766 (2022.01); G06V 10/776 (2022.01);
Abstract

A computer implemented method for detecting regression in a relationship between a performance indicator and AI metrics includes calculating a baseline threshold of regression degradation according to a historical correlation coefficient corresponding to a performance indicator and a set of AI metrics, calculating a current correlation coefficient according to one or more current data records, identifying a correction constant according to the current correlation coefficient and a desired correlation coefficient, generating a function to predict correction constants corresponding to performance indicator data and the set AI metrics, determining a delta correction constant for each AI metric of the set of AI metrics, applying the determined delta correction constant to the set of AI metrics, and identifying a subset of AI metric outliers according to the calculated baseline threshold and the determined delta correction constant.


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