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Cognition 128 (2013) 320330Contents lists available at Diverse ScienceDirectCognition journal homepage: www.elsevier.com/locate/COGNITDiscussionCan statistical learning bootstrap the integers? Lance

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What is can statistical learning bootstrap?

Bootstrap is a statistical method for estimating the sampling distribution of an estimator by resampling with replacement.

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Researchers and data scientists who are working on building predictive models using statistical learning techniques may use bootstrap for estimating the accuracy of their models.

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To perform bootstrap, one needs to repeatedly resample with replacement from the original data set and calculate the estimator of interest for each resampled data set.

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The purpose of bootstrap is to estimate the sampling distribution of a statistic, which can help in making inference about the population parameter.

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The results of the bootstrap analysis, including estimates of bias, variance, confidence intervals, and other relevant statistics.

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