[PDF.93pn] Theory of Disagreement-Based Active Learning (Foundations and Trends(r) in Machine Learning)
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Theory of Disagreement-Based Active Learning (Foundations and Trends(r) in Machine Learning)
Steve Hanneke
[PDF.wg25] Theory of Disagreement-Based Active Learning (Foundations and Trends(r) in Machine Learning)
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| #5357710 in Books | 2014-05-30 | Original language:English | PDF # 1 | 9.21 x.42 x6.14l,.63 | File type: PDF | 198 pages|
Active learning is a protocol for supervised machine learning in which a learning algorithm sequentially requests the labels of selected data points from a large pool of unlabeled data. This contrasts with passive learning where the labeled data are taken at random. The objective in active learning is to produce a highly-accurate classifier, ideally using fewer labels than the number of random labeled data sufficient for passive learning to achieve the same. Theory of D...
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