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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 ...
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.
Full details can be found in Help:Template, Wikipedia:Templates and m:Help:Advanced templates . 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 ...
Bootstrapping is any test or metric that uses random sampling with replacement (e.g. mimicking the sampling process), and falls under the broader class of resampling methods. Bootstrapping assigns measures of accuracy ( bias, variance, confidence intervals, prediction error, etc.) to sample estimates.
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This template is within the scope of WikiProject Sports, a collaborative effort to improve the coverage of sport-related topics on Wikipedia. If you would like to participate, please visit the project page, where you can join the discussion and see a list of open tasks. Sports Wikipedia:WikiProject Sports Template:WikiProject Sports sports articles
Wikipedia:Manual of Style/Layout. This page is about the layout of Wikipedia articles. For the layout of Wikipedia talk pages, see Wikipedia:Talk page layout. It is a generally accepted standard that editors should attempt to follow, though it is best treated with common sense, and occasional exceptions may apply.
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 ...