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ICML
2002
IEEE

Adaptive View Validation: A First Step Towards Automatic View Detection

10 years 6 months ago
Adaptive View Validation: A First Step Towards Automatic View Detection
Multi-view algorithms reduce the amount of required training data by partitioning the domain features into separate subsets or views that are sufficient to learn the target concept. Such algorithms rely on the assumption that the views are sufficiently compatible for multi-view learning (i.e., most examples are labeled identically in all views). In practice, it is unclear whether or not two views are sufficiently compatible for solving a new, unseen learning task. In order to cope with this problem, we introduce a view validation algorithm: given a learning task, the algorithm predicts whether or not the views are sufficiently compatible for solving that particular task. We use information acquired while solving several exemplar learning tasks to train a classifier that discriminates between the tasks for which the views are sufficiently and insufficiently compatible for multi-view learning. Our experiments on wrapper induction and text classification show that view validation require...
Ion Muslea, Steven Minton, Craig A. Knoblock
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2002
Where ICML
Authors Ion Muslea, Steven Minton, Craig A. Knoblock
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