Invention Application
- Patent Title: MOVING DECISION BOUNDARIES IN MACHINE LEARNING MODELS
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Application No.: US17308310Application Date: 2021-05-05
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Publication No.: US20220358397A1Publication Date: 2022-11-10
- Inventor: Oznur Alkan , Elizabeth Daly , Rahul Nair , Massimiliano Mattetti , Dennis Wei , Karthikeyan Natesan Ramamurthy
- 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
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N5/04

Abstract:
Embodiments are disclosed for a method. The method includes receiving feedback decision rules for multiple predictions by a trained machine learning model. generating a feedback rule set based on the feedback decision rules. The method further includes generating an updated training dataset based on an original training dataset and an updated feedback rule set. The updated feedback rule set resolves one or more conflicts of the feedback rule set, and the updated training dataset is configured to train the machine learning model to move a decision boundary. Generating the updated training dataset includes generating multiple updated training instances by applying one of the feedback decision rules to a training instance of the original training dataset.
Public/Granted literature
- US12106193B2 Moving decision boundaries in machine learning models Public/Granted day:2024-10-01
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