Deep supervised learning with mixture of neural networks.
Deep Neural Network (DNN), as a deep architectures, has shown excellent performance in classification tasks. However, when the data has different distributions or contains some latent non-observed factors, it is difficult for DNN to train a single model to perform well on the classification tasks. I...
| Published in: | Artificial Intelligence in Medicine Vol. 102 |
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| Main Authors: | , , , , |
| Format: | equations & formulas research tables/charts Journal Article |
| Published: |
Elsevier B.V.
Jan2020
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| Online Access: | View this record in EBSCOhost |