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  2. QLattice - Wikipedia

    en.wikipedia.org/wiki/QLattice

    The QLattice works with data in categorical and numeric format. It allows the user to quickly generate, plot and inspect mathematical formulae that can potentially explain the generating process of the data. It is designed for easy interaction with the researcher, allowing the user to guide the search based on their preexisting knowledge. [2] [6]

  3. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  4. Chi-square automatic interaction detection - Wikipedia

    en.wikipedia.org/wiki/Chi-square_automatic...

    Luchman, J.N.; CHAIDFOREST: Stata module to conduct random forest ensemble classification based on chi-square automated interaction detection (CHAID) as base learner, Available for free download, or type within Stata: ssc install chaidforest. IBM SPSS Decision Trees grows exhaustive CHAID trees as well as a few other types of trees such as CART.

  5. Multivariate adaptive regression spline - Wikipedia

    en.wikipedia.org/wiki/Multivariate_adaptive...

    In statistics, multivariate adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991. [1] It is a non-parametric regression technique and can be seen as an extension of linear models that automatically models nonlinearities and interactions between variables.

  6. Moderation (statistics) - Wikipedia

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

    To quantify the effect of a moderating variable in multiple regression analyses, regressing random variable Y on X, an additional term is added to the model. This term is the interaction between X and the proposed moderating variable. [1] Thus, for a response Y and two variables x 1 and moderating variable x 2,:

  7. Relevance vector machine - Wikipedia

    en.wikipedia.org/wiki/Relevance_vector_machine

    In mathematics, a Relevance Vector Machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and probabilistic classification. [1] A greedy optimisation procedure and thus fast version were subsequently developed.

  8. Segmented regression - Wikipedia

    en.wikipedia.org/wiki/Segmented_regression

    Segmented regression, also known as piecewise regression or broken-stick regression, is a method in regression analysis in which the independent variable is partitioned into intervals and a separate line segment is fit to each interval. Segmented regression analysis can also be performed on multivariate data by partitioning the various ...

  9. Multivariate statistics - Wikipedia

    en.wikipedia.org/wiki/Multivariate_statistics

    Multivariate regression attempts to determine a formula that can describe how elements in a vector of variables respond simultaneously to changes in others. For linear relations, regression analyses here are based on forms of the general linear model. Some suggest that multivariate regression is distinct from multivariable regression, however ...