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- Proactive_learning abstract "Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications.Active learning seeks to select the most informative unlabeled instances and ask an omniscient oracle for their labels, so as to retrain a learning algorithm maximizing accuracy. However, the oracle is assumed to be infallible (never wrong), indefatigable (always answers), individual (only one oracle), and insensitive to costs (always free or always charges the same). Proactive learning relaxes all four of these assumptions, relying on a decision-theoretic approach to jointly select the optimal oracle and instance, by casting the problem as a utility optimization problem subject to a budget constraint.".
- Proactive_learning wikiPageID "21985449".
- Proactive_learning wikiPageRevisionID "551939902".
- Proactive_learning hasPhotoCollection Proactive_learning.
- Proactive_learning subject Category:Learning.
- Proactive_learning subject Category:Machine_learning.
- Proactive_learning comment "Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications.Active learning seeks to select the most informative unlabeled instances and ask an omniscient oracle for their labels, so as to retrain a learning algorithm maximizing accuracy.".
- Proactive_learning label "Proactive learning".
- Proactive_learning sameAs m.05p6bnn.
- Proactive_learning sameAs Q7246814.
- Proactive_learning sameAs Q7246814.
- Proactive_learning wasDerivedFrom Proactive_learning?oldid=551939902.
- Proactive_learning isPrimaryTopicOf Proactive_learning.