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Learning to Classify

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Abstract

classifier is a procedure that accepts a set of features and produces a class label for them. Classifiers are immensely useful, and find wide application, because many problems are naturally classification problems. For example, if you wish to determine whether to place an advert on a web-page or not, you would use a classifier (i.e. look at the page, and say yes or no according to some rule). As another example, if you have a program that you found for free on the web, you would use a classifier to decide whether it was safe to run it (i.e. look at the program, and say yes or no according to some rule). As yet another example, credit card companies must decide whether a transaction is good or fraudulent.

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Forsyth, D. (2018). Learning to Classify. In: Probability and Statistics for Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-64410-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-64410-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64409-7

  • Online ISBN: 978-3-319-64410-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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