Definition
Bootstrap sampling is a process for creating a distribution of datasets out of a single dataset. It is used in the ensemble learning algorithm Bagging. It can also be used in algorithm evaluation to create a distribution of training sets from which to estimate properties of an algorithm.
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Recommended Reading
Davison, A. C., & Hinkley, D. (2006). Bootstrap methods and their applications (8th ed.). Cambridge: Cambridge Series in Statistical and Probabilistic Mathematics.
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(2011). Bootstrap Sampling. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_886
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DOI: https://doi.org/10.1007/978-0-387-30164-8_886
Publisher Name: Springer, Boston, MA
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Online ISBN: 978-0-387-30164-8
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