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:
Sep. 10, 2024

Filed:

Jan. 31, 2023
Applicant:

Dell Products L.p., Round Rock, TX (US);

Inventors:

Robert Anthony Lincourt, Jr., Franklin, MA (US);

Stephen James Todd, North Andover, MA (US);

Eloy Francisco Macha, Crowley, TX (US);

Assignee:

Dell Products, L.P., Round Rock, TX (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 7/00 (2006.01); G06F 16/00 (2019.01); G06F 16/2457 (2019.01); G06F 16/28 (2019.01);
U.S. Cl.
CPC ...
G06F 16/24573 (2019.01); G06F 16/285 (2019.01);
Abstract

A method and system for metadata-based feature expansion for automated machine learning processes. In machine learning, feature selection—or a method through model inputs are reduced in dimensionality by retaining the relevant features, while also discarding the noise, thereof—often plays a pivotal role in the availability of algorithm(s) to derive model(s) from, the optimizing of said model(s) through training and/or testing, and, ultimately, the reaching of acceptable performance thresholds evaluating said model(s), which leads to their implementation in solving real-world problems. Embodiments disclosed herein, accordingly, leverage captured dataset metadata, as well as graph techniques, to identify and suggest one or more supplemental features distinct from original features for, and yet relevant to, the real-world problem and any machine learning models being evaluated.


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