G06N 20/00 Machine learning
Introduced: January 2019
Description
G06N20/00 is the main group for machine learning, i.e. computing arrangements in which behaviour is derived from training data rather than fixed programming. It spans supervised, unsupervised and reinforcement learning workflows, including model training, validation and inference infrastructure. Kernel methods such as support vector machines are classified in G06N20/10 and ensemble techniques such as boosting or random forests in G06N20/20. Neural-network models as such belong to G06N3/00, and the application of learned models to pattern recognition tasks is covered by G06F18/00.
IPC and CPC are identically structured here. All 2 subcodes exist in both systems.
IPC defines codes here since 2019.
Child Classifications
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- G06N 20/10 using kernel methods, e.g. support vector machines [SVM] since 2019 IPC+CPC Available in IPC and CPC
Top Applicants
Top Applicants (IPC)
Class G06,2013–2023, worldwide · Source: EPO PATSTAT
- SAMSUNG ELECTRONICS COMPANY KR 66,669
- IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,313
- MICROSOFT TECHNOLOGY LICENSING US 41,918
- GOOGLE US 32,969
- SGCC(STATE GRID CORPORATION OF CHINA) 30,822
- INTEL CORPORATION US 30,010
- TENCENT TECHNOLOGY (SHENZHEN) COMPANY 28,235
- HUAWEI TECHNOLOGIES COMPANY CN 26,079
- APPLE US 21,891
- HUAWEI TECHNOLOGIES COMPANY 20,505
Top Applicants (CPC)
Class G06,2013–2023, worldwide · Source: EPO PATSTAT
- SAMSUNG ELECTRONICS COMPANY KR 76,952
- IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 62,841
- MICROSOFT TECHNOLOGY LICENSING US 44,778
- GOOGLE US 35,735
- INTEL CORPORATION US 32,087
- HUAWEI TECHNOLOGIES COMPANY CN 30,572
- TENCENT TECHNOLOGY (SHENZHEN) COMPANY 25,023
- APPLE US 23,482
- SGCC(STATE GRID CORPORATION OF CHINA) 22,548
- HUAWEI TECHNOLOGIES COMPANY 20,917