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  2. Bootstrapping (statistics) - Wikipedia

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

    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.

  3. Bootstrapping - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping

    Artificial intelligence and machine learning. Bootstrapping is a technique used to iteratively improve a classifier 's performance. Typically, multiple classifiers will be trained on different sets of the input data, and on prediction tasks the output of the different classifiers will be combined.

  4. Bootstrapping (linguistics) - Wikipedia

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

    Bootstrapping is a term used in language acquisition in the field of linguistics. It refers to the idea that humans are born innately equipped with a mental faculty that forms the basis of language. It is this language faculty that allows children to effortlessly acquire language. [1] As a process, bootstrapping can be divided into different ...

  5. Syntactic bootstrapping - Wikipedia

    en.wikipedia.org/wiki/Syntactic_bootstrapping

    Syntactic bootstrapping is a theory in developmental psycholinguistics and language acquisition which proposes that children learn word meanings by recognizing syntactic categories (such as nouns, adjectives, etc.) and the structure of their language. It is proposed that children have innate knowledge of the links between syntactic and semantic ...

  6. 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 ...

  7. Bootstrapping populations - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_populations

    Bootstrapping populations in statistics and mathematics starts with a sample observed from a random variable. When X has a given distribution law with a set of non fixed parameters, we denote with a vector , a parametric inference problem consists of computing suitable values – call them estimates – of these parameters precisely on the ...

  8. Bootstrapping (finance) - Wikipedia

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

    In finance, bootstrapping is a method for constructing a (zero-coupon) fixed-income yield curve from the prices of a set of coupon-bearing products, e.g. bonds and swaps.. A bootstrapped curve, correspondingly, is one where the prices of the instruments used as an input to the curve, will be an exact output, when these same instruments are valued using this curve.

  9. Semantic bootstrapping - Wikipedia

    en.wikipedia.org/wiki/Semantic_bootstrapping

    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] This theory proposes that children, when acquiring words, will recognize that words label ...