Invention Grant
- Patent Title: Personalized automated machine learning
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Application No.: US16805019Application Date: 2020-02-28
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Publication No.: US11379710B2Publication Date: 2022-07-05
- Inventor: Dakuo Wang , Chuang Gan , Ming Tan , Arunima Chaudhary , Lin Ju
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agent L. Jeffrey Kelly
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06K9/62 ; G06N3/08

Abstract:
In accordance with an embodiment of the invention, a method is provided for personalizing machine learning models for users of an automated machine learning system, the machine learning models being generated by an automated machine learning system. The method includes obtaining a first set of datasets for training first, second, and third neural networks, inputting the training datasets to the neural networks, tuning hyperparameters for the first, second, and third neural networks for testing and training the neural networks, inputting a second set of datasets to the trained neural networks and the third neural network generating a third output data including a relevance score for each of the users for each of the machine learning models, and displaying a list of machine learning models associated with each of the users, with each of the machine learning models showing the relevance score.
Public/Granted literature
- US20210271956A1 Personalized Automated Machine Learning Public/Granted day:2021-09-02
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