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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 ...
A template is a Wikipedia page created to be included in other pages. It usually contains repetitive material that may need to show up on multiple articles or pages, often with customizable input. Templates sometimes use MediaWiki parser functions, nicknamed " magic words ", a simple scripting language.
v. t. e. Responsive web design (RWD) or responsive design is an approach to web design that aims to make web pages render well on a variety of devices and window or screen sizes from minimum to maximum display size to ensure usability and satisfaction. [1][2] A responsive design adapts the web-page layout to the viewing environment [1] by using ...
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 ...
Template documentation. This template is used on approximately 1,100,000 pages, or roughly 2% of all pages. To avoid major disruption and server load, any changes should be tested in the template's /sandbox or /testcases subpages, or in your own user subpage. The tested changes can be added to this page in a single edit.
This guide presents the typical layout of Wikipedia articles, including the sections an article usually has, ordering of sections, and formatting styles for various elements of an article. For advice on the use of wiki markup, see Help:Editing; for guidance on writing style, see Manual of Style.
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.
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