Hyperparameter tuning in a database environment
US11868326B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 5, 2022 |
| Grant date | Jan 9, 2024 |
| Priority date | — |
| Expiry date | Dec 5, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An example method of tuning a machine learning operation can include receiving a data query comprising a reference to an input data set of a database, generating a plurality of unique sets of hyperparameters by varying a hyperparameter value of each set of hyperparameters of the plurality of unique sets of hyperparameters based on the input data set, in response to receiving the data query, training a plurality of machine learning models using the input data set of the data query, each of the plurality of machine learning models configured according to a respective one of a plurality of unique sets of hyperparameters, selecting a first machine learning model of the plurality of machine learning models based on an accuracy of an output of the first machine learning model, and returning the output of the first machine learning model in response to the data query.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.