Exponentiated Gradient Exploration for Active Learning
Active learning strategies respond to the costly labeling task in a supervised classification by selecting the most useful unlabeled examples in training a predictive model. Many conventional active learning algorithms focus on refining the decision boundary, rather than exploring new regions that c...
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-01-01
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| Series: | Computers |
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| Online Access: | http://www.mdpi.com/2073-431X/5/1/1 |