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公开(公告)号：US20240338608A1
公开(公告)日：2024-10-10
申请号：US18746289
申请日：2024-06-18
申请人： NEC Corporation
发明人： Mischa SCHMIDT , Julia Gastinger
CPC分类号： G06N20/00 , G06F9/3836 , G06F18/217 , G06F18/285
摘要： A method for automated machine learning includes controlling execution of a plurality of instantiations of different automated machine learning frameworks on a machine learning task each as a separate arm in consideration of available computational resources and time budget. During the execution by the separate arms, a plurality of machine learning models are trained and performance scores of the plurality of trained machine learning models are computed such that one or more of the plurality of trained machine learning models are selectable for the machine learning task based on the performance scores. This invention can be used for predicting patient discharge, predictive control in buildings for energy optimization, and so on.
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公开(公告)号：US20240338610A1
公开(公告)日：2024-10-10
申请号：US18749824
申请日：2024-06-21
申请人： NEC Corporation
发明人： Mischa SCHMIDT , Julia Gastinger
CPC分类号： G06N20/00 , G06F9/3836 , G06F18/217 , G06F18/285
摘要： A method for automated machine learning includes controlling execution of a plurality of instantiations of different automated machine learning frameworks on a machine learning task each as a separate arm in consideration of available computational resources and time budget. During the execution by the separate arms, a plurality of machine learning models are trained and performance scores of the plurality of trained machine learning models are computed such that one or more of the plurality of trained machine learning models are selectable for the machine learning task based on the performance scores. This invention can be used for predicting patient discharge, predictive control in buildings for energy optimization, and so on.
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