Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets

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Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets

Imbalanced class data is a common issue faced in classification tasks. Deep Belief Networks (DBN) is a promising deep learning algorithm when learning from complex feature input. However, when handling imbalanced class data, DBN encounters low performance as other machine learning algorithms. In thi...

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Bibliographic Details
Main Authors:	Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Mohammad, Omar Abdelaziz
Format:	Article
Language:	English English
Published:	2019
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://irep.iium.edu.my/77295/ http://irep.iium.edu.my/77295/1/Evolutionary%20deep%20belief%20networks%20with%20bootstrap%20sampling%20for%20imbalanced%20class%20datasets.pdf http://irep.iium.edu.my/77295/7/77295_Evolutionary%20deep%20belief%20networks%20with%20bootstrap%20sampling%20for%20imbalanced%20class%20datasets_Scopus.pdf

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