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  2. Statistical learning theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_learning_theory

    Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [ 1 ] [ 2 ] [ 3 ] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data.

  3. Computational statistics - Wikipedia

    en.wikipedia.org/wiki/Computational_statistics

    Though computational statistics is widely used today, it actually has a relatively short history of acceptance in the statistics community. For the most part, the founders of the field of statistics relied on mathematics and asymptotic approximations in the development of computational statistical methodology.

  4. Cramér's V - Wikipedia

    en.wikipedia.org/wiki/Cramér's_V

    In statistics, Cramér's V (sometimes referred to as Cramér's phi and denoted as φ c) is a measure of association between two nominal variables, giving a value between 0 and +1 (inclusive). It is based on Pearson's chi-squared statistic and was published by Harald Cramér in 1946.

  5. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R was started by professors Ross Ihaka and Robert Gentleman as a programming language to teach introductory statistics at the University of Auckland. [10] The language was inspired by the S programming language, with most S programs able to run unaltered in R. [6] The language was also inspired by Scheme's lexical scoping, allowing for local ...

  6. Rademacher complexity - Wikipedia

    en.wikipedia.org/wiki/Rademacher_complexity

    In computational learning theory (machine learning and theory of computation), Rademacher complexity, named after Hans Rademacher, measures richness of a class of sets with respect to a probability distribution. The concept can also be extended to real valued functions.

  7. Ensemble learning - Wikipedia

    en.wikipedia.org/wiki/Ensemble_learning

    Landmark learning is a meta-learning approach that seeks to solve this problem. It involves training only the fast (but imprecise) algorithms in the bucket, and then using the performance of these algorithms to help determine which slow (but accurate) algorithm is most likely to do best.

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  9. R Commander - Wikipedia

    en.wikipedia.org/wiki/R_Commander

    R Commander (Rcmdr) is a GUI for the R programming language, licensed under the GNU General Public License, and developed and maintained by John Fox in the sociology department at McMaster University. [2] Rcmdr looks and works similarly to SPSS GUI by providing a menu of analytic and graphical methods. It also displays the underlying R code ...

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