- 专利标题: Machine learning models based on altered data and systems and methods for training and using the same
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申请号: US16854107申请日: 2020-04-21
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公开(公告)号: US11861493B2公开(公告)日: 2024-01-02
- 发明人: Dmitry Vengertsev , Zahra Hosseinimakarem , Jonathan D. Harms
- 申请人: MICRON TECHNOLOGY, INC.
- 申请人地址: US ID Boise
- 专利权人: Micron Technology, Inc.
- 当前专利权人: Micron Technology, Inc.
- 当前专利权人地址: US ID Boise
- 代理机构: Dorsey & Whitney LLP
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06N3/04 ; G06F18/24 ; G06F18/214 ; G06V10/764 ; G06V10/82
摘要:
Data may be abstracted and/or masked prior to being provided to a machine learning model for training. A machine learning model may provide a confidence level associated with a result. If the confidence level is too high, the machine learning model or an application including the machine learning model may refrain from providing the result as an output. In some examples, the machine learning model may provide a “second best” result that has an acceptable confidence level. In other examples, an error signal may be provided as the output. In accordance with examples of the present disclosure, data may be abstracted and/or masked prior to being provided to a machine learning model for training and confidence levels of results of the trained machine learning model may be used to determine when a result should be withheld.
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