Invention Grant
- Patent Title: System and methods for iterative synthetic data generation and refinement of machine learning models
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Application No.: US16537882Application Date: 2019-08-12
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Publication No.: US11531883B2Publication Date: 2022-12-20
- Inventor: Eren Kursun
- Applicant: BANK OF AMERICA CORPORATION
- Applicant Address: US NC Charlotte
- Assignee: BANK OF AMERICA CORPORATION
- Current Assignee: BANK OF AMERICA CORPORATION
- Current Assignee Address: US NC Charlotte
- Agency: Moore & Van Allen PLLC
- Agent Nicholas C. Russell
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06K9/62 ; G06N3/04 ; G06N20/20

Abstract:
Embodiments of the present invention provide an improvement to convention machine model training techniques by providing an innovative system, method and computer program product for the generation of synthetic data using an iterative process that incorporates multiple machine learning models and neural network approaches. A collaborative system for receiving data and continuously analyzing the data to determine emerging patterns is provided. Common characteristics of data from the identified emerging patterns are broadened in scope and used to generate a synthetic data set using a generative neural network approach. The resulting synthetic data set is narrowed based on analysis of the synthetic data as compared to the detected emerging patterns, and can then be used to further train one or more machine learning models for further pattern detection.
Public/Granted literature
- US20210049455A1 SYSTEM AND METHODS FOR ITERATIVE SYNTHETIC DATA GENERATION AND REFINEMENT OF MACHINE LEARNING MODELS Public/Granted day:2021-02-18
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