Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets

• 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/77295/1/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; http://irep.iium.edu.my/77295/

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...