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In statistics, bag of little bootstraps refers to a scalable bootstrap that runs resampling on many small subsamples and averages the results, giving bootstrap-quality uncertainty for massive data. This meaning comes from Kleiner (2014) in Journal of the Royal Statistical Society Series B: Statistical Methodology.[1]
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