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  2. Bootstrap aggregating - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_aggregating

    If nā€²=n, then for large n the set is expected to have the fraction (1 - 1/e) (ā‰ˆ63.2%) of the unique examples of D, the rest being duplicates. This kind of sample is known as a bootstrap sample. Sampling with replacement ensures each bootstrap is independent from its peers, as it does not depend on previous chosen samples when sampling.

  3. 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.

  4. Bootstrapping - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping

    In computer technology, the term bootstrapping refers to language compilers that are able to be coded in the same language. (For example, a C compiler is now written in the C language. Once the basic compiler is written, improvements can be iteratively made, thus pulling the language up by its bootstraps).

  5. Bootstrapping (compilers) - Wikipedia

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

    Bootstrapping (compilers) In computer science, bootstrapping is the technique for producing a self-compiling compiler ā€“ that is, a compiler (or assembler) written in the source programming language that it intends to compile. An initial core version of the compiler (the bootstrap compiler) is generated in a different language (which could be ...

  6. Bootstrap error-adjusted single-sample technique - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_error-adjusted...

    Bootstrap error-adjusted single-sample technique. In statistics, the bootstrap error-adjusted single-sample technique ( BEST or the BEAST) is a non-parametric method that is intended to allow an assessment to be made of the validity of a single sample. It is based on estimating a probability distribution representing what can be expected from ...

  7. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    The approximation of a normal distribution with a Monte Carlo method. Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle.

  8. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    However, Wright did not give examples of his technique's use, making it hard to verify that he described the modern notion of median. The median (in the context of probability) certainly appeared in the correspondence of Christiaan Huygens, but as an example of a statistic that was inappropriate for actuarial practice.

  9. CSS framework - Wikipedia

    en.wikipedia.org/wiki/CSS_framework

    CSS framework. A CSS framework is a library allowing for easier, more standards-compliant web design using the Cascading Style Sheets language. Most of these frameworks contain at least a grid. More functional frameworks also come with more features and additional JavaScript based functions, but are mostly design oriented and focused around ...