Learning under differing training and test distributions
One of the main problems in machine learning is to train a predictive model from training data and to make predictions on test data. Most predictive models are constructed under the assumption that the training data is governed by the exact same distribution which the model will later be exposed to....
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| Format: | Doctoral Thesis |
| Language: | English |
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Universität Potsdam
2008
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| Online Access: | http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-33331 http://opus.kobv.de/ubp/volltexte/2009/3333/ |