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  2. Bootstrapping (statistics) - Wikipedia

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

    Bootstrapping (statistics) Bootstrapping is a procedure for estimating the distribution of an estimator by resampling (often with replacement) one's data or a model estimated from the data. [1] Bootstrapping assigns measures of accuracy (bias, variance, confidence intervals, prediction error, etc.) to sample estimates. [2][3] This technique ...

  3. Master boot record - Wikipedia

    en.wikipedia.org/wiki/Master_boot_record

    Information contained in the partition table of an external hard drive as it appears in the utility program QtParted, running under Linux (with KDE) In addition to the bootstrap code and a partition table, master boot records may contain a disk signature. This is a 32-bit value that is intended to identify uniquely the disk medium (as opposed ...

  4. 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. As of May 2023, Bootstrap is the 17th most starred ...

  5. Resampling (statistics) - Wikipedia

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

    The best example of the plug-in principle, the bootstrapping method. Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio ...

  6. Bootstrap aggregating - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_aggregating

    v. t. e. Bootstrap aggregating, also called bagging (from b ootstrap agg regat ing), is a machine learning ensemble meta-algorithm designed to improve the stability and accuracy of machine learning algorithms used in statistical classification and regression. It also reduces variance and helps to avoid overfitting.

  7. Conformal bootstrap - Wikipedia

    en.wikipedia.org/wiki/Conformal_bootstrap

    The conformal bootstrap is a non-perturbative mathematical method to constrain and solve conformal field theories, i.e. models of particle physics or statistical physics that exhibit similar properties at different levels of resolution.

  8. Pivotal quantity - Wikipedia

    en.wikipedia.org/wiki/Pivotal_quantity

    Pivotal quantity. In statistics, a pivotal quantity or pivot is a function of observations and unobservable parameters such that the function's probability distribution does not depend on the unknown parameters (including nuisance parameters). [1] A pivot need not be a statistic — the function and its 'value' can depend on the parameters of ...

  9. Bootstrapping - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping

    Bootstrapping was also expanded upon in the book Bootstrap Business by Richard Christiansen, the Harvard Business Review article The Art of Bootstrapping and the follow-up book The Origin and Evolution of New Businesses by Amar Bhide. There is also an entire bible written on how to properly bootstrap by Seth Godin.