Missing Data Problems in Machine Learning
Learning, inference, and prediction in the presence of missing data are pervasive problems in machine learning and statistical data analysis. This thesis focuses on the problems of collaborative prediction with non-random missing data and classification with missing features. We begin by presenting...
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| Format: | Others |
| Language: | en_ca |
| Published: |
2008
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| Online Access: | http://hdl.handle.net/1807/11232 |