Patent · US Active

Feature crossing for machine learning

US12346656B2 · kind B2 · utility

0Cited by

0References

20Claims

0Family size

Assignee

Lemon Inc. · KR

Inventors

Qingyi Lu · Los Angeles, US
Yuan Gao · San Diego, US
Hongyu Xiong · Los Angeles, US
Han Wang · Los Angeles, US
Bin Liu · Nanhu, CN
Xiangyu Zeng · Los Angeles, US
Rui Li · Los Angeles, US
Yiqi FENG · Los Angeles, US

Key dates

Filing date	May 5, 2022
Grant date	Jul 1, 2025
Priority date	—
Expiry date	Jul 2, 2043

Classification

Technology area (CPC G)Physics
CPC primaryG06N20/00
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Embodiments of the present disclosure relate to feature crossing for machine learning. According to example embodiments of the present disclosure, a method comprises determining a semantic correlation relationship between a plurality of feature categories, the semantic correlation relationship indicating respective degrees of semantic correlation between respective pairs of feature categories among the plurality of feature categories; obtaining at least two features classified in at least two of the plurality of feature categories for machine learning; and performing feature crossing on the at least two features based on the semantic correlation relationship.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.