Supervised Classification Leveraging Refined Unlabeled Data
This thesis focuses on how unlabeled data can improve supervised learning classi-fiers in all contexts, for both scarce to abundant label situations. This is meant toaddress the limitations within supervised learning with regards to label availability.Extending the training set with unlabeled data c...
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| Format: | Others |
| Language: | English |
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Linköpings universitet, Institutionen för datavetenskap
2015
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119320 |