Active Learning in Black-Box Settings
Active learning refers to the settings in which a machine learning algorithm (learner) is able to select data from which it learns (selecting points and then obtaining their labels), and by doing so aims to achieve better accuracy (e.g., by avoiding obtaining training data that is redundant or unimp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Austrian Statistical Society
2016-02-01
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| Series: | Austrian Journal of Statistics |
| Online Access: | http://www.ajs.or.at/index.php/ajs/article/view/204 |