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- Q4677561 subject Q7015116.
- Q4677561 abstract "Active learning is a special case of semi-supervised machine learning in which a learning algorithm is able to interactively query the user (or some other information source) to obtain the desired outputs at new data points. In statistics literature it is sometimes also called optimal experimental design.There are situations in which unlabeled data is abundant but manually labeling is expensive. In such a scenario, learning algorithms can actively query the user/teacher for labels. This type of iterative supervised learning is called active learning. Since the learner chooses the examples, the number of examples to learn a concept can often be much lower than the number required in normal supervised learning. With this approach, there is a risk that the algorithm be overwhelmed by uninformative examples.Recent developments are dedicated to hybrid active learning and active learning in a single-pass (on-line) context, combining concepts from the field of Machine Learning (e.g., conflict and ignorance) with adaptive, incremental learning policies in the field of Online machine learning.".
- Q4677561 wikiPageExternalLink ActiveIntelligence.org.
- Q4677561 wikiPageExternalLink al-rs.
- Q4677561 wikiPageExternalLink Rubens-Active-Learning-RecSysHB2010.pdf.
- Q4677561 wikiPageExternalLink ~active_learning.
- Q4677561 wikiPageWikiLink Q1041418.
- Q4677561 wikiPageWikiLink Q180684.
- Q4677561 wikiPageWikiLink Q282453.
- Q4677561 wikiPageWikiLink Q6760393.
- Q4677561 wikiPageWikiLink Q7015116.
- Q4677561 wikiPageWikiLink Q7094097.
- Q4677561 wikiPageWikiLink Q7098942.
- Q4677561 wikiPageWikiLink Q7246814.
- Q4677561 wikiPageWikiLink Q815577.
- Q4677561 comment "Active learning is a special case of semi-supervised machine learning in which a learning algorithm is able to interactively query the user (or some other information source) to obtain the desired outputs at new data points. In statistics literature it is sometimes also called optimal experimental design.There are situations in which unlabeled data is abundant but manually labeling is expensive. In such a scenario, learning algorithms can actively query the user/teacher for labels.".
- Q4677561 label "Active learning (machine learning)".