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:
Jan. 13, 2026

Filed:

Dec. 16, 2020
Applicant:

Teradata Us, Inc., San Diego, CA (US);

Inventors:

Awny Kayed Al-Omari, Cedar Park, TX (US);

Maksym Sergiyovych Oblogin, Austin, TX (US);

Khaled Bouaziz, Round Rock, TX (US);

Michael James Hanlon, Austin, TX (US);

Kashif Abdullah Siddiqui, Round Rock, TX (US);

Assignee:

Teradata US, Inc., San Diego, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/126 (2023.01); G06F 16/25 (2019.01); G06F 16/28 (2019.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 3/126 (2013.01); G06F 16/25 (2019.01); G06F 16/284 (2019.01); G06N 20/00 (2019.01);
Abstract

Hyperparameter tuning for a machine learning model is performed in a massively parallel database system. A computer system comprised of a plurality of compute units executes a relational database management system (RDBMS), wherein the RDBMS manages a relational database comprised of one or more tables storing data. One or more of the compute units perform the hyperparameter tuning for the machine learning model, wherein the hyperparameters are control parameters used in construction of the model, and the tuning of the hyperparameters is implemented as an operation in the RDBMS that accepts training and scoring data for the model, constructs the model using the hyperparameters and the training data, and generates goodness metrics for the model using the scoring data.


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