[PDF.93pn] Theory of Disagreement-Based Active Learning (Foundations and Trends(r) in Machine Learning)

Theory of Disagreement-Based Active Learning (Foundations and Trends(r) in Machine Learning)

[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

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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...

You can specify the type of files you want, for your device.Theory of Disagreement-Based Active Learning (Foundations and Trends(r) in Machine Learning)   |  Steve Hanneke. Which are the reasons I like to read books. Great story by a great author.

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