Difference between revisions of "Semi-supervised learning"
From Cohen Courses
Jump to navigationJump to search (Blanked the page) |
|||
| Line 1: | Line 1: | ||
| + | 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. | ||
| + | == Relevant Papers == | ||
| + | |||
| + | {{#ask: [[UsesMethod::Semi-supervised learning]] | ||
| + | | ?AddressesProblem | ||
| + | | ?UsesDataset | ||
| + | }} | ||
Latest revision as of 11:22, 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.
