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:
Aug. 01, 2023

Filed:

Sep. 21, 2016
Applicant:

Equifax, Inc., Atlanta, GA (US);

Inventors:

Jeffrey Q. Ouyang, Atlanta, GA (US);

Vickey Chang, Suwanee, GA (US);

Rupesh Patel, Atlanta, GA (US);

Trevis J. Litherland, Alpharetta, GA (US);

Assignee:

EQUIFAX INC., Atlanta, GA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 17/18 (2006.01); G06F 16/28 (2019.01); G06Q 10/063 (2023.01); G06N 7/01 (2023.01); G06Q 40/03 (2023.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 16/285 (2019.01); G06F 17/18 (2013.01); G06N 7/01 (2023.01); G06Q 10/063 (2013.01); G06Q 40/03 (2023.01);
Abstract

Certain aspects involve updating data structures to indicate relationships between attribute trends and response variables used for training automated modeling systems. For example, a data structure stores data for training an automated modeling algorithm. The training data includes attribute values for multiple entities over a time period. A computing system generates, for each entity, at least one trend attribute that is a function of a respective time series of attribute values. The computing system modifies the data structure to include the generated trend attributes and updates the training data to include trend attribute values for the trend attributes. The computing system trains the automated modeling algorithm with the trend attribute values from the data structure. In some aspects, trend attributes are generated by applying a frequency transform to a time series of attribute values and selecting, as trend attributes, some of the coefficients generated by the frequency transform.


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