INTEGRATING DEEP LEARNING INTO GENERALIZED ADDITIVE MIXED-EFFECT (GAME) FRAMEWORKS
user-5d4bc4a8530c70a9b361c870(2019)
摘要
In an example embodiment, knowledge discovery using deep learning is combined with the scalability and personalization capabilities of generalized additive mixed effect (GAME) modeling. Specifically, features learned in a last fully connected layer of a deep learning model may be used to augment features used in a fixed or random effects training portion of a GAME model.
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关键词
Personalization,Deep learning,Knowledge extraction,Scalability,Layer (object-oriented design),Artificial intelligence,Computer science,Random effects model,Mixed effects
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