Difference between revisions of "Semi-supervised learning"
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− | + | This is a [[category::Method]] of machine learning, where a small set of labeled data is used to train a classifier which also makes use of a much larger set of unlabeled data. One popular version of semi-supervised learning is [http://en.wikipedia.org/wiki/Co-training co-training], introduced by Avrim Blum and Tom Mitchell in 1998. | |
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+ | == Relevant Papers == | ||
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+ | {{#ask: [[UsesMethod::Semi-supervised learning]] | ||
+ | | ?AddressesProblem | ||
+ | | ?UsesDataset | ||
+ | }} |
Latest revision as of 10:22, 3 October 2012
This is a Method of machine learning, where a small set of labeled data is used to train a classifier which also makes use of a much larger set of unlabeled data. One popular version of semi-supervised learning is co-training, introduced by Avrim Blum and Tom Mitchell in 1998.