Active Learning Query Strategies for Classification, Regression, and Clustering: A Survey

Generally, data is available abundantly in unlabeled form, and its annotation requires some cost. The labeling, as well as learning cost, can be minimized by learning with the minimum labeled data instances. Active learning (AL), learns from a few labeled data instances with the additional facility...

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Vydáno v:	Journal of computer science and technology Ročník 35; číslo 4; s. 913 - 945
Hlavní autoři:	Kumar, Punit, Gupta, Atul
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Singapore Springer Singapore 01.07.2020 Springer Springer Nature B.V Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, Madhya Pradesh 482005, India
Témata:	Active learning Annotations Artificial Intelligence Classification Clustering Computational linguistics Computer Science Data Structures and Information Theory Deep learning Information Systems Applications (incl.Internet) Labels Language processing Mathematical analysis Natural language interfaces Numerical analysis Queries Software Engineering Survey Surveys Theory of Computation deep active learning active regression active learning active classification active learning query strategy active clustering
ISSN:	1000-9000, 1860-4749
On-line přístup:	Získat plný text
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