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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| Main Authors: | , , |
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| Format: | EJournal Article |
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Universitas Ahmad Dahlan,
2019-07-26.
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| Subjects: | |
| Online Access: | Get Fulltext |
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| Call Number: |
A1234.567 |
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| Copy 1 | Available |