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:
Apr. 09, 2024

Filed:

May. 16, 2023
Applicant:

Home Depot Product Authority, Llc, Atlanta, GA (US);

Inventors:

Matthew Hagen, Atlanta, GA (US);

Estelle Afshar, Atlanta, GA (US);

Huiming Qu, Atlanta, GA (US);

Ala Eddine Ayadi, Atlanta, GA (US);

Jiaqi Wang, Atlanta, GA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/20 (2019.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 18/23 (2023.01); G06N 20/00 (2019.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06N 20/20 (2019.01); G06F 18/2148 (2023.01); G06F 18/2155 (2023.01); G06F 18/217 (2023.01); G06F 18/23 (2023.01); G06N 20/00 (2019.01); G06V 10/763 (2022.01); G06V 10/764 (2022.01); G06V 10/7747 (2022.01); G06V 10/82 (2022.01);
Abstract

A method for machine learning-based classification may include training a machine learning model with a full training data set, the full training data set comprising a plurality of data points, to generate a first model state of the machine learning model, generating respective embeddings for the data points in the full training data set with the first model state of the machine learning model, applying a clustering algorithm to the respective embeddings to generate one or more clusters of the embeddings, identifying outlier embeddings from the one or more clusters of the embeddings, generating a reduced training data set comprising the full training data set less the data points associated with the outlier embeddings, training the machine learning model with the reduced training data set to a second model state, and applying the second model state to one or more data sets to classify the one or more data sets.


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