Empirical comparison of competing query learning methods
N Abe, H Mamitsuka, A Nakamura - … , DS'98 Fukuoka, Japan, December 14 …, 1998 - Springer
N Abe, H Mamitsuka, A Nakamura
Discovey Science: First International Conference, DS'98 Fukuoka, Japan …, 1998•SpringerQuery learning is a form of machine learning in which the learner has control over the
learning data it receives. In the context of discovery science, query learning may prove to be
relevant in at least two ways. One is as a method of selective sampling, when a huge set of
unlabeled data is available but a relatively small number of these data can be labeled, and a
method that can selectively ask valuable queries is desired. The other is as a method of
experimental design, where a query learning method is used to inform the experimenter …
learning data it receives. In the context of discovery science, query learning may prove to be
relevant in at least two ways. One is as a method of selective sampling, when a huge set of
unlabeled data is available but a relatively small number of these data can be labeled, and a
method that can selectively ask valuable queries is desired. The other is as a method of
experimental design, where a query learning method is used to inform the experimenter …
Abstract
Query learning is a form of machine learning in which the learner has control over the learning data it receives. In the context of discovery science, query learning may prove to be relevant in at least two ways. One is as a method of selective sampling, when a huge set of unlabeled data is available but a relatively small number of these data can be labeled, and a method that can selectively ask valuable queries is desired. The other is as a method of experimental design, where a query learning method is used to inform the experimenter what experiments are to be performed next
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