GENERATING NEW MACHINE LEARNING MODELS BASED ON COMBINATIONS OF HISTORICAL FEATURE-EXTRACTION RULES AND HISTORICAL MACHINE-LEARNING MODELS
Techniques for generating new machine learning (ML) systems are described. In an example, a computer system receives a request specifying a task and a performance metric for the new ML model via a user interface. In response, the computer system dynamically generates new feature-extraction rules and...
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Main Author | |
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Format | Patent |
Language | English |
Published |
28.11.2019
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Subjects | |
Online Access | Get full text |
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Summary: | Techniques for generating new machine learning (ML) systems are described. In an example, a computer system receives a request specifying a task and a performance metric for the new ML model via a user interface. In response, the computer system dynamically generates new feature-extraction rules and new machine learning models based on a rule-model combination that would perform the specified task at a level meeting or exceeding the performance metric. |
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Bibliography: | Application Number: US201815986043 |