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Capital One ML Patent: Dataset Performance Change Using Machine Learning

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Summary

The USPTO granted US Patent 12608446B2 to Capital One Services, LLC covering methods for determining performance change within datasets using machine learning models. The patent addresses training machine learning models on control datasets and applying test datasets to detect performance shifts attributable to applied conditions. The patent was filed December 21, 2021, with Application No. 17557599, and contains 14 claims.

Published by USPTO on changeflow.com . Detected, standardized, and enriched by GovPing. Review our methodology and editorial standards .

What changed

The USPTO issued Patent 12608446B2 to Capital One Services, LLC for methods determining performance shifts in datasets due to applied conditions using machine learning. The invention trains an ML model on a control dataset and uses it with a test dataset to isolate performance changes attributable to specific conditions versus environmental factors.

Competitors developing similar ML-based dataset performance monitoring systems should review the patent claims to assess potential licensing needs or design-around options. The patent's broad claim scope covering two-dataset comparison methods for detecting condition-induced performance changes may capture a wide range of analytics implementations.

Archived snapshot

Apr 21, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Grants

Determining performance change within a dataset with an applied condition using machine learning models

Grant US12608446B2 Kind: B2 Apr 21, 2026

Assignee

Capital One Services, LLC

Inventors

Tong Niu, Abhishek Kumar Shrivastava, Ruoyu Shao

Abstract

Methods and systems are disclosed for determining a performance shift due to an applied condition, excluding other, e.g., environmental, factors. One mechanism for determining a performance shift due to an applied condition involves using two datasets (e.g., a control dataset and a test dataset) for two different populations. A training dataset is used to train a machine learning model to build a control dataset to be used in a second machine learning model together with a test dataset to determine whether a performance shift between the two datasets is due to the condition that was applied to the test dataset.

CPC Classifications

G06N 20/20 G06N 3/08 G06N 5/01 G06N 7/01 G06N 20/00 G06F 18/217 G06F 18/214

Filing Date

2021-12-21

Application No.

17557599

Claims

14

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Last updated

Classification

Agency
USPTO
Published
April 21st, 2026
Instrument
Notice
Branch
Executive
Legal weight
Binding
Stage
Final
Change scope
Minor
Document ID
US12608446B2

Who this affects

Applies to
Technology companies
Industry sector
5112 Software & Technology
Activity scope
Patent grant Machine learning Dataset analysis
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence Machine Learning

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