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Abstract: Concept drift is an important characteristic and inevitable difficult problem in streaming data mining. Ensemble learning is commonly used to deal with concept drift. However, most ensemble ...
Ensemble deep learning models enhance early diagnosis of Alzheimer's disease using neuroimaging data
EDL combines the outputs of several machine learning (ML) models to enhance their generalization performance. The traditional approach to building an ensemble uses deep neural networks (DNNs) in a ...
ABSTRACT: When a customer uses the software, then it is possible to occur defects that can be removed in the updated versions of the software. Hence, in the present work, a robust examination of cross ...
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