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  2. Bradley Efron - Wikipedia

    en.wikipedia.org/wiki/Bradley_Efron

    Bradley Efron (/ ˈ ɛ f r ən /; born May 24, 1938) [1] is an American statistician. Efron has been president of the American Statistical Association (2004) and of the Institute of Mathematical Statistics (1987–1988). [2]

  3. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    The bootstrap sample is taken from the original by using sampling with replacement (e.g. we might 'resample' 5 times from [1,2,3,4,5] and get [2,5,4,4,1]), so, assuming N is sufficiently large, for all practical purposes there is virtually zero probability that it will be identical to the original "real" sample. This process is repeated a large ...

  4. Out-of-bag error - Wikipedia

    en.wikipedia.org/wiki/Out-of-bag_error

    One set, the bootstrap sample, is the data chosen to be "in-the-bag" by sampling with replacement. The out-of-bag set is all data not chosen in the sampling process. When this process is repeated, such as when building a random forest, many bootstrap samples and OOB sets are created. The OOB sets can be aggregated into one dataset, but each ...

  5. Resampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Resampling_(statistics)

    Subsampling is an alternative method for approximating the sampling distribution of an estimator. The two key differences to the bootstrap are: the resample size is smaller than the sample size and; resampling is done without replacement. The advantage of subsampling is that it is valid under much weaker conditions compared to the bootstrap.

  6. Particle filter - Wikipedia

    en.wikipedia.org/wiki/Particle_filter

    From 1950 to 1996, all the publications on particle filters, and genetic algorithms, including the pruning and resample Monte Carlo methods introduced in computational physics and molecular chemistry, present natural and heuristic-like algorithms applied to different situations without a single proof of their consistency, nor a discussion on the bias of the estimates and genealogical and ...

  7. Bootstrap aggregating - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_aggregating

    Bootstrap aggregating, also called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and accuracy of ML classification and regression algorithms.

  8. Code folding - Wikipedia

    en.wikipedia.org/wiki/Code_folding

    As a manual method, token-based folding allows discretion in grouping code based on arbitrary criteria, such as "functions related to a given task", which cannot be inferred from syntactic analysis. Token-based folding requires in-band signalling, with folding tokens essentially being structured comments, and unlike other methods, are present ...

  9. Bootstrap (front-end framework) - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_(front-end...

    Bootstrap (formerly Twitter Bootstrap) is a free and open-source CSS framework directed at responsive, mobile-first front-end web development. It contains HTML , CSS and (optionally) JavaScript -based design templates for typography , forms , buttons , navigation , and other interface components.