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:
Oct. 01, 2024

Filed:

May. 02, 2023
Applicant:

Wells Fargo Bank, N.a., San Francisco, CA (US);

Inventors:

Agus Sudjianto, Charlotte, NC (US);

Aijun Zhang, Island E, HK;

Zebin Yang, Island E, HK;

Assignee:

Wells Fargo Bank, N.A., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 11/20 (2006.01); G06F 30/20 (2020.01); G06N 20/20 (2019.01); G06Q 10/067 (2023.01); G06Q 30/0201 (2023.01); G06Q 30/0204 (2023.01); G06Q 40/03 (2023.01);
U.S. Cl.
CPC ...
G06T 11/206 (2013.01); G06F 30/20 (2020.01); G06N 20/20 (2019.01); G06Q 10/067 (2013.01); G06Q 30/0205 (2013.01); G06Q 30/0206 (2013.01); G06Q 40/03 (2023.01);
Abstract

Systems, apparatuses, methods, and computer program products are disclosed for generating a single-index model (SIM) tree. An example method includes receiving a data set and a maximum tree depth. The example method further includes screening a set of variables from the data set to form split variables. The method may include, while maximum tree depth has not been reached, (i) generating a fast SIM estimation for nodes of a tree level, (ii) for each node, selecting a split point and split variable based on the fast SIM estimation, (iii) based on the selected split points and split variables, generating nodes for a next tree level, each including a subset of data, and (iv) repeating steps (i), (ii), and (iii). The method may include fitting a SIM for each leaf node at maximum tree depth based on a subset of the data set represented by the leaf node.


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