Invention Grant
- Patent Title: Systems and methods for automatically building a machine learning model
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Application No.: US17971519Application Date: 2022-10-21
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Publication No.: US11934971B2Publication Date: 2024-03-19
- Inventor: Aleksandr Kotolyan
- Applicant: Digital Lion, LLC
- Applicant Address: US CA Los Angeles
- Assignee: DIGITAL LION, LLC
- Current Assignee: DIGITAL LION, LLC
- Current Assignee Address: US CA Los Angeles
- Agency: Lewis Roca Rothgerber Christie LLP
- Main IPC: G06N7/01
- IPC: G06N7/01 ; G06F3/0482 ; G06F17/18 ; G06N20/20

Abstract:
Systems and methods for automatically building a machine learning model are disclosed. A plurality of variables is displayed via a graphical user interface (GUI). A target variable and a first independent variable are identified from the plurality of variables. A parameter associated with the machine learning model is identified. Collected data is received via the GUI. A first machine learning model is built using as inputs, the parameter and the collected data associated with the first independent variable and the target variable. A change is made to at least a portion of the inputs used to build the first machine learning model. A second machine learning model is built based on the change. A prediction accuracy of the first machine learning model is compared to the prediction accuracy of the second machine learning model. Either the first or second machine learning model is selected based on the prediction accuracy.
Public/Granted literature
- US20230048301A1 SYSTEMS AND METHODS FOR AUTOMATICALLY BUILDING A MACHINE LEARNING MODEL Public/Granted day:2023-02-16
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