Invention Application
- Patent Title: HYPERPARAMETER TUNING IN A DATABASE ENVIRONMENT
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Application No.: US18074830Application Date: 2022-12-05
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Publication No.: US20230136738A1Publication Date: 2023-05-04
- Inventor: Boxin Jiang , Qiming Jiang
- Applicant: SNOWFLAKE INC.
- Applicant Address: US MT Bozeman
- Assignee: SNOWFLAKE INC.
- Current Assignee: SNOWFLAKE INC.
- Current Assignee Address: US MT Bozeman
- Main IPC: G06F16/21
- IPC: G06F16/21 ; G06N3/08 ; G06F16/242 ; G06F16/2458

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.
Public/Granted literature
- US11868326B2 Hyperparameter tuning in a database environment Public/Granted day:2024-01-09
Information query