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In general, bootstrapping usually refers to a self-starting process that is supposed to continue or grow without external input. Many analytical techniques are often called bootstrap methods in reference to their self-starting or self-supporting implementation, such as bootstrapping (statistics), bootstrapping (finance), or bootstrapping (linguistics).
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. It also reduces variance and overfitting.
The studentized bootstrap, also called bootstrap-t, is computed analogously to the standard confidence interval, but replaces the quantiles from the normal or student approximation by the quantiles from the bootstrap distribution of the Student's t-test (see Davison and Hinkley 1997, equ. 5.7 p. 194 and Efron and Tibshirani 1993 equ 12.22, p. 160):
In literal terms, a bootstrap is the small strap on a boot that is used to help pull on the entire boot. Similarly in computer science, booting refers to the startup of an operation system by means of first initiating a smaller program. Therefore, bootstrapping refers to the leveraging of a small action into a more powerful and significant ...
Bootstrapping (law), a former rule of evidence in U.S. federal conspiracy trials; Bootstrapping (linguistics), a term used in language acquisition; Bootstrapping (statistics), a method for assigning measures of accuracy to sample estimates; Bootstrap aggregating, a method used to improve the stability and accuracy of machine learning algorithms
Boot is short for bootstrap [1] [2] or bootstrap load and derives from the phrase to pull oneself up by one's bootstraps. [3] [4] The usage calls attention to the requirement that, if most software is loaded onto a computer by other software already running on the computer, some mechanism must exist to load the initial software onto the ...
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Semantic bootstrapping is a linguistic theory of child language acquisition which proposes that children can acquire the syntax of a language by first learning and recognizing semantic elements and building upon, or bootstrapping from, that knowledge. [1]